8. Laboratories

8. Laboratories

BIC01. Introduction to Computing (Mandatory) 1st Sem, Lab: 4 hr(s)

Basic Computing Lab:

  • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
  • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
  • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
  • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

BCH101. Chemistry I (Mandatory) 1st Sem, Lab: 2 hr(s)

Chemistry Lab:

  • Equipment: Analytical balances, microscopes, spectrophotometers, glassware kits.
  • Safety: Fume hoods, emergency showers, chemical spill kits.
  • Reagents: Acids/bases, buffers, organic solvents, pH indicators.

CS112. Objects-oriented programming I (Mandatory) 2nd Sem, Lab: 4 hr(s)

Basic Computing Lab:

  • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
  • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
  • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
  • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

BFI101. Physics I (Mandatory) 2nd Sem, Lab: 4 hr(s)

Physics Laboratory:

  • Equipment and Tools: Optical benches, force tables, pendulums, dynamic carts, spectrometers, PASCO sensors, and measurement modules (multimeters, power supplies, calipers).
  • Hardware and Technology: Academic-use laptops, Arduino sensors, and modules for data acquisition.
  • Software: Arduino IDE, MATLAB for analysis, Microsoft Office, and specialized experimental data acquisition software.
  • Services and Experiments: Physics I and II lab sessions (Mechanics, Thermodynamics, Electromagnetism, Waves), instrumentation training, and support for research projects.

CS113. Objects-oriented programming II (Mandatory) 3rd Sem, Lab: 2 hr(s)

Basic Computing Lab:

  • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
  • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
  • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
  • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

CS2B1. Platform Based Development (Mandatory) 3rd Sem, Lab: 2 hr(s)

Advanced Computing Lab:

  • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
  • OS: Linux (Fedora) / Windows 11 Pro.
  • Programming: C++20, Python (SciPy stack), Perl, R.
  • Software:
    • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
    • DB/Cloud: PostgreSQL, MongoDB, Docker.
    • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

    AI161. Applied AI (Mandatory) 3rd Sem, Lab: 4 hr(s)

    Basic Computing Lab:

    • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
    • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
    • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
    • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

    CS210. Algorithms and Data Structures (Mandatory) 4th Sem, Lab: 2 hr(s)

    Advanced Computing Lab:

    • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
    • OS: Linux (Fedora) / Windows 11 Pro.
    • Programming: C++20, Python (SciPy stack), Perl, R.
    • Software:
      • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
      • DB/Cloud: PostgreSQL, MongoDB, Docker.
      • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

      CS211. Theory of Computation (Mandatory) 4th Sem, Lab: 2 hr(s)

      Basic Computing Lab:

      • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
      • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
      • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
      • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

      CS221. Computer Systems Architecture (Mandatory) 4th Sem, Lab: 4 hr(s)

      Networks & Cybersecurity Lab:

      • Hardware: 30 PCs + dedicated network racks (Cisco switches/routers, Raspberry Pi clusters).
      • OS: Linux (Kali, CentOS) / Windows Server.
      • Software: Wireshark, GNS3, VMware ESXi, 8086 emulators.
      • Focus: Network simulation, penetration testing, IoT protocols.

      CS271. Data Management (Mandatory) 4th Sem, Lab: 4 hr(s)

      Advanced Computing Lab:

      • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
      • OS: Linux (Fedora) / Windows 11 Pro.
      • Programming: C++20, Python (SciPy stack), Perl, R.
      • Software:
        • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
        • DB/Cloud: PostgreSQL, MongoDB, Docker.
        • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

        CS212. Analysis and Design of Algorithms (Mandatory) 5th Sem, Lab: 2 hr(s)

        Advanced Computing Lab:

        • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
        • OS: Linux (Fedora) / Windows 11 Pro.
        • Programming: C++20, Python (SciPy stack), Perl, R.
        • Software:
          • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
          • DB/Cloud: PostgreSQL, MongoDB, Docker.
          • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

          CS261. Artificial Intelligence (Mandatory) 5th Sem, Lab: 2 hr(s)

          Basic Computing Lab:

          • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
          • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
          • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
          • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

          CS272. Databases II (Mandatory) 5th Sem, Lab: 2 hr(s)

          Advanced Computing Lab:

          • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
          • OS: Linux (Fedora) / Windows 11 Pro.
          • Programming: C++20, Python (SciPy stack), Perl, R.
          • Software:
            • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
            • DB/Cloud: PostgreSQL, MongoDB, Docker.
            • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

            CS291. Software Engineering I (Mandatory) 5th Sem, Lab: 2 hr(s)

            Advanced Computing Lab:

            • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
            • OS: Linux (Fedora) / Windows 11 Pro.
            • Programming: C++20, Python (SciPy stack), Perl, R.
            • Software:
              • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
              • DB/Cloud: PostgreSQL, MongoDB, Docker.
              • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

              CS2S1. Operating systems (Mandatory) 5th Sem, Lab: 2 hr(s)

              Advanced Computing Lab:

              • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
              • OS: Linux (Fedora) / Windows 11 Pro.
              • Programming: C++20, Python (SciPy stack), Perl, R.
              • Software:
                • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                • DB/Cloud: PostgreSQL, MongoDB, Docker.
                • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                CS231. Networking and Communication (Mandatory) 6th Sem, Lab: 2 hr(s)

                Advanced Computing Lab:

                • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                • OS: Linux (Fedora) / Windows 11 Pro.
                • Programming: C++20, Python (SciPy stack), Perl, R.
                • Software:
                  • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                  • DB/Cloud: PostgreSQL, MongoDB, Docker.
                  • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                  CS311. Algorithms for Complex Problems (Mandatory) 6th Sem, Lab: 2 hr(s)

                  Basic Computing Lab:

                  • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
                  • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
                  • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
                  • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

                  CS312. Advanced Data Structures (Mandatory) 6th Sem, Lab: 2 hr(s)

                  Advanced Computing Lab:

                  • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                  • OS: Linux (Fedora) / Windows 11 Pro.
                  • Programming: C++20, Python (SciPy stack), Perl, R.
                  • Software:
                    • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                    • DB/Cloud: PostgreSQL, MongoDB, Docker.
                    • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                    CS342. Compilers (Mandatory) 6th Sem, Lab: 2 hr(s)

                    Advanced Computing Lab:

                    • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                    • OS: Linux (Fedora) / Windows 11 Pro.
                    • Programming: C++20, Python (SciPy stack), Perl, R.
                    • Software:
                      • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                      • DB/Cloud: PostgreSQL, MongoDB, Docker.
                      • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                      AI263. Introduction to Machine Learning (Mandatory) 6th Sem, Lab: 4 hr(s)

                      Basic Computing Lab:

                      • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
                      • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
                      • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
                      • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

                      FI201. Computational Physics (Mandatory) 6th Sem, Lab: 2 hr(s)

                      Physics Laboratory:

                      • Equipment and Tools: Optical benches, force tables, pendulums, dynamic carts, spectrometers, PASCO sensors, and measurement modules (multimeters, power supplies, calipers).
                      • Hardware and Technology: Academic-use laptops, Arduino sensors, and modules for data acquisition.
                      • Software: Arduino IDE, MATLAB for analysis, Microsoft Office, and specialized experimental data acquisition software.
                      • Services and Experiments: Physics I and II lab sessions (Mechanics, Thermodynamics, Electromagnetism, Waves), instrumentation training, and support for research projects.

                      CS251. Computer Graphics (Mandatory) 7th Sem, Lab: 4 hr(s)

                      Advanced Computing Lab:

                      • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                      • OS: Linux (Fedora) / Windows 11 Pro.
                      • Programming: C++20, Python (SciPy stack), Perl, R.
                      • Software:
                        • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                        • DB/Cloud: PostgreSQL, MongoDB, Docker.
                        • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                        CS292. Software Engineering II (Mandatory) 7th Sem, Lab: 2 hr(s)

                        Advanced Computing Lab:

                        • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                        • OS: Linux (Fedora) / Windows 11 Pro.
                        • Programming: C++20, Python (SciPy stack), Perl, R.
                        • Software:
                          • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                          • DB/Cloud: PostgreSQL, MongoDB, Docker.
                          • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                          CS2H1. User Experience (UX) (Mandatory) 7th Sem, Lab: 4 hr(s)

                          Basic Computing Lab:

                          • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
                          • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
                          • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
                          • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

                          AI264. Deep Learning (Mandatory) 7th Sem, Lab: 4 hr(s)

                          Basic Computing Lab:

                          • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
                          • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
                          • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
                          • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

                          CS3I1. Computer Security (Mandatory) 8th Sem, Lab: 2 hr(s)

                          Advanced Computing Lab:

                          • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                          • OS: Linux (Fedora) / Windows 11 Pro.
                          • Programming: C++20, Python (SciPy stack), Perl, R.
                          • Software:
                            • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                            • DB/Cloud: PostgreSQL, MongoDB, Docker.
                            • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                            CS3P1. Parallel and Distributed Computing (Mandatory) 8th Sem, Lab: 2 hr(s)

                            Advanced Computing Lab:

                            • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                            • OS: Linux (Fedora) / Windows 11 Pro.
                            • Programming: C++20, Python (SciPy stack), Perl, R.
                            • Software:
                              • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                              • DB/Cloud: PostgreSQL, MongoDB, Docker.
                              • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                              CS402. Capstone Project I (Mandatory) 8th Sem, Lab: 4 hr(s)

                              Advanced Computing Lab:

                              • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                              • OS: Linux (Fedora) / Windows 11 Pro.
                              • Programming: C++20, Python (SciPy stack), Perl, R.
                              • Software:
                                • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                AI268. Computational Vision (Elective) 8th Sem, Lab: 2 hr(s)

                                Advanced Computing Lab:

                                • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                • OS: Linux (Fedora) / Windows 11 Pro.
                                • Programming: C++20, Python (SciPy stack), Perl, R.
                                • Software:
                                  • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                  • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                  • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                  CS393. Information systems (Elective) 8th Sem, Lab: 2 hr(s)

                                  Advanced Computing Lab:

                                  • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                  • OS: Linux (Fedora) / Windows 11 Pro.
                                  • Programming: C++20, Python (SciPy stack), Perl, R.
                                  • Software:
                                    • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                    • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                    • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                    CS370. Big Data (Mandatory) 9th Sem, Lab: 2 hr(s)

                                    Advanced Computing Lab:

                                    • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                    • OS: Linux (Fedora) / Windows 11 Pro.
                                    • Programming: C++20, Python (SciPy stack), Perl, R.
                                    • Software:
                                      • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                      • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                      • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                      CS403. Capstone Project II (Mandatory) 9th Sem, Lab: 4 hr(s)

                                      Advanced Computing Lab:

                                      • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                      • OS: Linux (Fedora) / Windows 11 Pro.
                                      • Programming: C++20, Python (SciPy stack), Perl, R.
                                      • Software:
                                        • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                        • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                        • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                        AI365. Advanced Generative AI Models (Mandatory) 9th Sem, Lab: 4 hr(s)

                                        Basic Computing Lab:

                                        • Hardware: 30 workstations (Intel Core i5, 8GB RAM, 256GB SSD, integrated graphics/sound, Gigabit Ethernet).
                                        • OS: Dual-boot Linux (Ubuntu LTS) / Windows 11 Pro.
                                        • Programming: Python, Java, C++ (C++11/14/17), C#, Prolog, Lex/Yacc.
                                        • Tools: Git, VS Code, Eclipse, Jupyter Notebook.

                                        AI369. Robotics (Elective) 9th Sem, Lab: 2 hr(s)

                                        Advanced Computing Lab:

                                        • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                        • OS: Linux (Fedora) / Windows 11 Pro.
                                        • Programming: C++20, Python (SciPy stack), Perl, R.
                                        • Software:
                                          • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                          • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                          • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                          CS351. Topics in Computer Graphics (Elective) 9th Sem, Lab: 2 hr(s)

                                          Advanced Computing Lab:

                                          • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                          • OS: Linux (Fedora) / Windows 11 Pro.
                                          • Programming: C++20, Python (SciPy stack), Perl, R.
                                          • Software:
                                            • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                            • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                            • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                            CS353. Quantum Computing (Elective) 9th Sem, Lab: 2 hr(s)

                                            Advanced Computing Lab:

                                            • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                            • OS: Linux (Fedora) / Windows 11 Pro.
                                            • Programming: C++20, Python (SciPy stack), Perl, R.
                                            • Software:
                                              • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                              • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                              • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                              CS392. Tópicos en Ingeniería de Software (Elective) 9th Sem, Lab: 2 hr(s)

                                              Advanced Computing Lab:

                                              • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                              • OS: Linux (Fedora) / Windows 11 Pro.
                                              • Programming: C++20, Python (SciPy stack), Perl, R.
                                              • Software:
                                                • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                                • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                                • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                                CS3P3. Internet of Things (Elective) 9th Sem, Lab: 4 hr(s)

                                                Advanced Computing Lab:

                                                • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                                • OS: Linux (Fedora) / Windows 11 Pro.
                                                • Programming: C++20, Python (SciPy stack), Perl, R.
                                                • Software:
                                                  • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                                  • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                                  • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                                  CS3P2. Cloud Computing (Mandatory) 10th Sem, Lab: 2 hr(s)

                                                  Advanced Computing Lab:

                                                  • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                                  • OS: Linux (Fedora) / Windows 11 Pro.
                                                  • Programming: C++20, Python (SciPy stack), Perl, R.
                                                  • Software:
                                                    • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                                    • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                                    • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                                    CS404. Research Workshop (Mandatory) 10th Sem, Lab: 4 hr(s)

                                                    Advanced Computing Lab:

                                                    • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                                    • OS: Linux (Fedora) / Windows 11 Pro.
                                                    • Programming: C++20, Python (SciPy stack), Perl, R.
                                                    • Software:
                                                      • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                                      • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                                      • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                                      AI367. Topics in Artificial Intelligence (Mandatory) 10th Sem, Lab: 2 hr(s)

                                                      Advanced Computing Lab:

                                                      • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                                      • OS: Linux (Fedora) / Windows 11 Pro.
                                                      • Programming: C++20, Python (SciPy stack), Perl, R.
                                                      • Software:
                                                        • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                                        • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                                        • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                                        AI368. Evolutionary Computing (Mandatory) 10th Sem, Lab: 2 hr(s)

                                                        Advanced Computing Lab:

                                                        • Hardware: 30 high-end PCs (Intel Core i7, 16GB RAM, 512GB NVMe SSD, NVIDIA GTX 1660, Gigabit Ethernet).
                                                        • OS: Linux (Fedora) / Windows 11 Pro.
                                                        • Programming: C++20, Python (SciPy stack), Perl, R.
                                                        • Software:
                                                          • Development: J2EE, .NET 6, MATLAB, GCC/Clang.
                                                          • DB/Cloud: PostgreSQL, MongoDB, Docker.
                                                          • Specialized: Rational Rose, VTK, LEDA, 8086 emulators. itemize

                                                          ACM (2008). Digital Libray. Association for Computing Machinery. http://portal.acm.org/dl.cfm.
                                                          ACM (2018). Acm code of ethics and professional conduct. Technical report, ACM.
                                                          ACM (2019). Guidelines for extracurricular activities in computing. Technical report, ACM.
                                                          ACM and IEEE-CS (2017). Information technology curricula 2017. Technical report, ACM and IEEE-CS.
                                                          ACM Data Science Task Force (2021). Computing competencies for undergraduate data science curricula. Technical report, Association for Computing Machinery (ACM).
                                                          ACM/IEEE-CS (2020). Computing curricula 2020. Technical report, ACM Press and IEEE Computer Society Press.
                                                          ACM/IEEE-CS Joint Task Force on Cybersecurity Education (2017). Cybersecurity curricula 2017. Technical report, ACM Press and IEEE Computer Society Press and Association for Information Systems Special Interest Group on Information Security and Privacy (AIS SIGSEC) and International Federation for Information Processing Technical Committee on Information Security Education (IFIP WG 11.8).
                                                          ACM/IEEE-CS/AAAI Joint Task Force (2023). Cs2023: Acm/ieee-cs/aaai computer science curricula. Technical report, ACM Press and IEEE Computer Society Press and AAAI Press.
                                                          Agrawal, D. et al. (2023). Toward a systems architecture for ai-enabled applications. Communications of the ACM, 66(6):54–63.
                                                          Aho, A. V., Lam, M. S., Sethi, R., and Ullman, J. D. (2006). Compilers: Principles, Techniques, and Tools. Pearson, 2nd edition.
                                                          Alpaydin, E. (2020). Introduction to Machine Learning. MIT Press, 4th edition.
                                                          Aluru, S., editor (2006). Handbook of Computational Molecular Biology. Computer and Information Science Series. Chapman & Hall, CRC, Boca Raton, FL.
                                                          Anderson, R. J. (2020). Security Engineering: A Guide to Building Dependable Distributed Systems. Wiley, 3rd edition.
                                                          Angel, E. and Shreiner, D. (2014). Interactive Computer Graphics: A Top-Down Approach with WebGL. Pearson, 7th edition.
                                                          Apostol, T. M. (1997). Calculus, Vol. II: Multi-Variable Calculus and Linear Algebra with Applications. John Wiley & Sons, 2nd edition.
                                                          Appel, A. W. (2004). Modern Compiler Implementation in Java. Cambridge University Press, 2nd edition.
                                                          Arpaci-Dusseau, R. H. and Arpaci-Dusseau, A. C. (2018). Operating Systems: Three Easy Pieces. Arpaci-Dusseau Books, 1.0 edition.
                                                          Baase, S. and Henry, T. (2017). A Gift of Fire: Social, Legal, and Ethical Issues for Computing Technology. Pearson, 5th edition.
                                                          Back, T. (1996). Evolutionary Algorithms in Theory and Practice. Oxford University Press.
                                                          Bass, L., Clements, P., and Kazman, R. (2021). Software Architecture in Practice. Addison-Wesley Professional, 4th edition.
                                                          Beaulieu, A. (2009). Learning SQL. O'Reilly Media, 2nd edition.
                                                          Bender, E. M., Gebru, T., et al. (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT '21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. Foundational paper on AI ethics with ongoing relevance.
                                                          Bernstein, P. A., Hadzilacos, V., and Goodman, N. (1987). Concurrency Control and Recovery in Database Systems. Addison-Wesley.
                                                          Bill, C. and Matei, Z. (2018). Spark: The Definitive Guide: Big Data Processing Made Simple. O'Reilly Media, Sebastopol, CA.
                                                          Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer.
                                                          Bondi, A. B. (2015). Foundations of Software and System Performance Engineering: Process, Performance Modeling, Requirements, Testing, Scalability, and Practice. Addison-Wesley, Upper Saddle River, NJ.
                                                          Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford University Press.
                                                          Bravyi, S., Dial, O., Gambetta, J. M., Gil, D., and Nazario, Z. (2022). Quantum algorithms for fixed qubit architectures. Nature Reviews Physics, 4(8):499–512. Survey on quantum algorithms for optimization and simulation with near-term devices.
                                                          Brook, P. (1968). The Empty Space: A Book About the Theatre. Penguin Books.
                                                          Brookshear, J. G. and Brylow, D. (2019a). Computer Science: An Overview. Pearson, global edition edition.
                                                          Brookshear, J. G. and Brylow, D. (2019b). Computer Science: An Overview. Pearson, global edition edition.
                                                          Brown, T. L., Jr., H. E. L., Bursten, B. E., Murphy, C. J., and Woodward, P. M. (2017). Chemistry: The Central Science. Pearson.
                                                          Burden, R. L. and Faires, J. D. (2010). Numerical Analysis. Cengage Learning.
                                                          Burns, B., Beda, J., Hightower, K., and Evenson, L. (2022). Kubernetes: Up and Running. O'Reilly Media, 3rd edition.
                                                          Buyya, R. and Dastjerdi, A. V. (2016). Internet of Things: Principles and Paradigms. Morgan Kaufmann.
                                                          Buyya, R., Vecchiola, C., and Selvi, S. T. (2013). Mastering Cloud Computing: Foundations and Applications Programming. Morgan Kaufmann, 1st edition.
                                                          Cambridge (2006). Diccionario Inglés-Espanol Cambridge. Editorial Oxford.
                                                          Campbell, A. B. (2001). Historia general del teatro en el Perú. Universidad de San Martín de Porres.
                                                          Cardona, P. and Lombardi, P. G. (2002). Cómo desarrollar las Competencias de Liderazgo. PAD, Lima, 3rd edition.
                                                          Cardona, P. and na, C. R. P. (2008). Dirección por misiones: Cómo generar empresas de alto rendimiento. Deusto.
                                                          Cardona, P. and Wilkinson, H. (2009). Creciendo como Líder. Ediciones Universidad de Navarra EUNSA.
                                                          Chang, R. and Goldsby, K. A. (2016). Chemistry. McGraw-Hill Education.
                                                          Chapra, S. C. and Canale, R. P. (2015). Numerical Methods for Engineers. McGraw-Hill Education.
                                                          Chinchilla, N. and Moragas, M. (2007). Dueños de Nuestro Destino. Editorial Ariel.
                                                          Chollet, F. (2021). Deep Learning with Python. Manning, 2nd edition.
                                                          CiteSeer.IST (2008). Scientific Literature Digital Libray. College of Information Sciences and Technology, Penn State University. http://citeseer.ist.psu.edu.
                                                          Clote, P. and Backofen, R. (2000). Computational Molecular Biology: An Introduction. John Wiley & Sons Ltd. 279 pages.
                                                          Cloud, A. (2024). AI Ethics and best practices in chinese context. Chinese perspective on AI ethics and implementation guidelines.
                                                          Commission, A. C. A. (2022). Abet criteria for student professional development. Technical report, ABET.
                                                          Committee, I. E. (2019). Ethical dilemmas in engineering. Technical report, IEEE.
                                                          Cooper, K. and Torczon, L. (2011). Engineering a Compiler. Morgan Kaufmann, 2nd edition.
                                                          Cormen, T. H., Leiserson, C. E., Rivest, R. L., and Stein, C. (2009). Introduction to Algorithms. MIT Press, 3rd edition.
                                                          Cormen, T. H., Leiserson, C. E., Rivest, R. L., and Stein, C. (2022). Introduction to Algorithms. MIT Press, 4th edition.
                                                          Corporation, N. (2024). Cuda c++ programming guide. https://docs.nvidia.com/cuda/cuda-c-programming-guide/. Documentación oficial de NVIDIA.
                                                          Craig, J. J. (2017). Introduction to Robotics: Mechanics and Control. Pearson, 4th edition.
                                                          Cuadros-Vargas, E., Romero, R. A. F., Mock, M., and Brisaboa, N. (2004). Implementing data structures: An incremental approach. Available at: http://socios.spc.org.pe/ecuadros/cursos/pdfs/.
                                                          Dasgupta, S., Papadimitriou, C., and Vazirani, U. (2006). Algorithms. McGraw-Hill Education.
                                                          de Educación de la ACM, C. (2022). Guía para prácticas pre-profesionales exitosas en ciencia de la computación. Technical report, Association for Computing Machinery. Documento oficial con estándares para prácticas en computación.
                                                          Deb, K. (2001). Multi-Objective Optimization using Evolutionary Algorithms. Wiley.
                                                          DeepSeek (2024). Deepseek model documentation and best practices. Official documentation for DeepSeek AI models and usage guidelines.
                                                          Deitel, H. and Deitel, P. (2017). C++17: The Complete Guide. Pearson, Boston, MA, 10th edition.
                                                          Devore, J. L. (2016). Probability and Statistics for Engineering and the Sciences. Cengage Learning.
                                                          Dianine-Havard, A. (2007). Virtuous Leadership: An Agenda for Personal Excellence. Scepter Publishers.
                                                          D'Souza, A. (1994). Discover Your Leadership Style. St. Pauls.
                                                          Duckett, J. (2014). JavaScript and JQuery: Interactive Front-End Web Development. Wiley.
                                                          Díaz-Herrera, J. L. and Hilburn, T. B. (2004). Software engineering: Curriculum Guidelines for Undergraduate Degree Programs in Software Engineering. Technical report, ACM, IEEE.
                                                          Eiben, A. E. and Smith, J. E. (2015). Introduction to Evolutionary Computing. Springer, 2nd edition.
                                                          Eilam, E. (2005). Reversing: Secrets of Reverse Engineering. Wiley, Indianapolis, IN.
                                                          Elmasri, R. and Navathe, S. B. (2015). Fundamentals of Database Systems. Pearson, 7th edition.
                                                          Ferreiro, P. and Alcázar, M. (2009). Gobierno de Personas en la Empresa. Ediciones Universidad de Navarra EUNSA.
                                                          Fielding, R. T. (2000). Architectural Styles and the Design of Network-based Software Architectures. PhD thesis, University of California, Irvine.
                                                          Flanagan, D. (2020). JavaScript: The Definitive Guide. O'Reilly Media, 7th edition.
                                                          Force, A. E. T. (2020). Case studies in computing and society. Technical report, ACM.
                                                          Foster, D. (2022). Generative Deep Learning. O'Reilly Media, 2nd edition.
                                                          Fowler, M. (2017). Refactoring: Improving the Design of Existing Code. Addison-Wesley, 2nd edition.
                                                          Fowler, M. (2018). Refactoring: Improving the Design of Existing Code. Addison-Wesley Professional, 2nd edition.
                                                          Gaede, V. and Günther, O. (1998). Multidimensional access methods. ACM Computing Surveys, 30(2):170–231.
                                                          Gamma, E., Helm, R., Johnson, R., and Vlissides, J. (1994a). Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional, Reading, MA, 1st edition.
                                                          Gamma, E., Helm, R., Johnson, R., and Vlissides, J. M. (1994b). Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional.
                                                          Garcia-Molina, H., Ullman, J. D., and Widom, J. (2008). Database Systems: The Complete Book. Pearson, 2nd edition.
                                                          Gasca, J. (2021). Web Security for Developers. No Starch Press.
                                                          Goleman, D. (2006). Emotional Intelligence: Why It Can Matter More Than IQ. Bantam Books.
                                                          Gonzalez, R. C. and Woods, R. E. (2018). Digital Image Processing. Pearson, 4th edition.
                                                          Goodfellow, I., Bengio, Y., and Courville, A. (2016a). Deep Learning. MIT Press.
                                                          Goodfellow, I., Bengio, Y., and Courville, A. (2016b). Deep Learning. MIT Press.
                                                          Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. (2014). Generative adversarial networks. In NeurIPS.
                                                          Google (2024). Introduction to responsible ai. Google's updated framework for responsible AI development and use.
                                                          Gregg, B. (2020). Systems Performance: Enterprise and the Cloud. Addison-Wesley Professional, Boston, MA, 2nd edition.
                                                          Grimaldi, R. P. (2003). Discrete and Combinatorial Mathematics: An Applied Introduction. Pearson, 5th edition.
                                                          Grotowski, J. (1970). Towards a Poor Theatre. Simon and Schuster.
                                                          Guttag, J. V. (2013). Introduction to Computation and Programming Using Python. MIT Press, 1st edition.
                                                          Géron, A. (2022). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. O'Reilly, 3rd edition.
                                                          Halim, S. and Halim, F. (2020). Competitive Programming 4: The Lower Bound of Programming Contests. Lulu.
                                                          Hanes, D., Salgueiro, G., and Grossetete, P. (2017). IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things. Cisco Press.
                                                          Harris, D. and Harris, S. (2012). Digital Design and Computer Architecture. Morgan Kaufmann, 2nd edition.
                                                          Hastie, T., Tibshirani, R., and Friedman, J. (2009). The Elements of Statistical Learning. Springer, 2nd edition.
                                                          Hawkins, P. (2011). Leadership Team Coaching: Developing Collective Transformational Leadership. Kogan Page.
                                                          He, K., Zhang, X., Ren, S., and Sun, J. (2016). Deep residual learning for image recognition. CVPR, pages 770–778.
                                                          Hearn, D., Baker, M. P., and Carithers, W. (2014). Computer Graphics with OpenGL. Pearson, 4th edition.
                                                          Hecht, E. (2017). Optics. Pearson.
                                                          Hellman, E. (2013). Android Programming: Pushing the Limits. Wiley.
                                                          Herlihy, M. and Shavit, N. (2012). The Art of Multiprocessor Programming. Morgan Kaufmann, revised 1st edition.
                                                          Herlihy, M., Shavit, N., Luchangco, V., and Spear, M. (2020). The Art of Multiprocessor Programming. Morgan Kaufmann, 2nd edition.
                                                          Hersey, P., Blanchard, K. H., and Johnson, D. E. (2007). Management of Organizational Behavior: Leading Human Resources. Prentice Hall, 9th edition.
                                                          Hopcroft, J. E., Motwani, R., and Ullman, J. D. (2013). Introduction to Automata Theory, Languages, and Computation. Pearson, 3rd edition.
                                                          Huete, L. M. (2008). Construye tu Sueño. LID Editorial Empresarial.
                                                          Hunsaker, P. (2001). Training in Management Skills. Pearson Prentice Hall.
                                                          Hunt, A. and Thomas, D. (1999). The Pragmatic Programmer: From Journeyman to Master. Addison-Wesley, 1st edition.
                                                          IBM Research (2023). Ibm quantum hardware roadmap. Technical report, IBM Research. Accedido: 2026-02-13. La página original ha sido movida o actualizada.
                                                          IEEE (2020). Ieee code of ethics. Technical report, IEEE.
                                                          IEEE-Computer Society (2008). Digital Libray. IEEE-Computer Society. http://www.computer.org/publications/dlib.
                                                          Institute, T. R. (2024). Ai development in china: Current status and future trends. Technical report, Tencent Research Institute. Comprehensive analysis of Chinese AI ecosystem development.
                                                          Johnson, J. (2013). Designing with the Mind in Mind. Morgan Kaufmann, 2nd edition.
                                                          Johnson, J. (2020). Designing with the Mind in Mind: Simple Guide to Understanding User Interface Design Guidelines. Morgan Kaufmann, 3rd edition.
                                                          Josuttis, N. M. (2019). C++17: The Complete Guide. Pearson Education, Indianapolis, IN, 1st edition.
                                                          Jurafsky, D. and Martin, J. H. (2024). Speech and Language Processing. Prentice Hall, 3rd edition.
                                                          Karau, H., Konwinski, A., Wendell, P., and Zaharia, M. (2017). Learning Spark: Lightning-Fast Big Data Analysis. O'Reilly Media.
                                                          Kim, G., Humble, J., Debois, P., and Willis, J. (2016). The DevOps Handbook. IT Revolution Press.
                                                          Kim, G., Humble, J., Debois, P., Willis, J., and Forsgren, N. (2021). The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations. IT Revolution Press, 2nd edition.
                                                          Kirk, D. B. and mei W. Hwu, W. (2016). Programming Massively Parallel Processors: A Hands-on Approach. Morgan Kaufmann, Cambridge, MA, 3rd edition.
                                                          Kleinberg, J. and Tardos, É. (2005). Algorithm Design. Pearson.
                                                          Kleppmann, M. (2017a). Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. O'Reilly Media.
                                                          Kleppmann, M. (2017b). Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. O'Reilly Media.
                                                          Kleppner, D. and Kolenkow, R. J. (2013). An Introduction to Mechanics. Cambridge University Press, 2nd edition.
                                                          Knuth, D. E. (1997a). The Art of Computer Programming, Volume 1: Fundamental Algorithms. Addison-Wesley, 3rd edition.
                                                          Knuth, D. E. (1997b). The Art of Computer Programming, Volume 1: Fundamental Algorithms. Addison-Wesley Professional, 3rd edition.
                                                          Kozen, D. C. (2006). Theory of Computation. Springer.
                                                          Krogh, A., Brown, M., Mian, I. S., Sjölander, K., and Haussler, D. (1994). Hidden markov models in computational biology, applications to protein modeling. J Mol. Biol, 235:1501–1531.
                                                          Kurose, J. and Ross, K. (2021). Computer Networking: A Top-Down Approach. Pearson, 8th edition.
                                                          Laaksonen, A. (2020). Competitive Programmer's Handbook. Draft.
                                                          Larson, R. and Edwards, B. H. (2014). Calculus. Cengage Learning.
                                                          Laudon, K. C. and Laudon, J. P. (2021). Management Information Systems: Managing the Digital Firm. Pearson, 17th edition.
                                                          LaValle, S. M. (2023). Virtual Reality. Cambridge University Press.
                                                          Lay, D. C., Lay, S. R., and McDonald, J. J. (2016). Linear Algebra and Its Applications. Pearson.
                                                          LeBlanc, R., Sobel, A., Ben-Menachem, M., Lethbridge, T. C., Díaz-Herrera, J. L., Hilburn, T. B., McGettrick, A., Atlee, J. M., Hawthorne, E. K., Leaney, J., Budgen, D., Matsumoto, Y., Thompson, J. B., Ardis, M., Hislop, G., Offutt, J., Sebern, M., and Visser, W. (2015). Curriculum Guidelines for Undergraduate Degree Programs in Software Engineering. Technical report, IEEE Computer Society, ACM.
                                                          Lehman, E., Leighton, F. T., and Meyer, A. R. (2018). Mathematics for Computer Science. MIT OpenCourseWare.
                                                          Lencioni, P. (2002). The Five Dysfunctions of a Team: A Leadership Fable. Jossey-Bass.
                                                          Lin, J. and Dyer, C. (2010). Data-Intensive Text Processing with MapReduce. Morgan and Claypool Publishers.
                                                          Luger, G. F. (2008). Artificial Intelligence: Structures and Strategies for Complex Problem Solving. Pearson, 6th edition.
                                                          MacGrew, J. (1999). Focus on Grammar Basic. Editorial Oxford.
                                                          Majorana, A. (1958). El arte de hablar en público. La España Moderna.
                                                          Manning, C. D., Raghavan, P., and Schütze, H. (2008). Introduction to Information Retrieval. Cambridge University Press.
                                                          Marinescu, D. C. (2022). Cloud Computing: Theory and Practice. Morgan Kaufmann, 3rd edition.
                                                          Marschner, S. and Shirley, P. (2021a). Fundamentals of Computer Graphics. A K Peters/CRC Press, 5th edition.
                                                          Marschner, S. and Shirley, P. (2021b). Fundamentals of Computer Graphics. CRC Press, 5th edition. Same book as Marschner2021; alternate citation key using lead author Shirley.
                                                          Marsden, J. E. and Tromba, A. (2011). Vector Calculus. W. H. Freeman and Company, 6th edition.
                                                          Matei, Z., Mosharaf, C., Tathagata, D., Ankur, D., Justin, M., Murphy, M., J, F. M., Scott, S., and Ion, S. (2012). Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing. In Proceedings of the 9th USENIX Symposium on Networked Systems Design and Implementation (NSDI), San Jose, CA. USENIX Association.
                                                          Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., and Galstyan, A. (2021). A survey on bias and fairness in machine learning. ACM Computing Surveys, 54(6).
                                                          mei W. Hwu, W., Kirk, D. B., and Hajj, I. E. (2022). Programming Massively Parallel Processors: A Hands-on Approach. Morgan Kaufmann, 4th edition.
                                                          Meyers, S. (2014). Effective Modern C++: 42 Specific Ways to Improve Your Use of C++11 and C++14. O'Reilly Media, Sebastopol, CA, 1st edition.
                                                          Microsoft (2024). Prompt crafting for ai systems. Official Microsoft prompt engineering guidance updated for 2024.
                                                          Mikolov, T., Chen, K., Corrado, G., and Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv preprint. arXiv:1301.3781.
                                                          Miravalles, L. (1998). Iniciación al teatro: teoría y práctica. San Pablo.
                                                          Mitchell, M. (1998). An Introduction to Genetic Algorithms. MIT Press.
                                                          Mollick, E. (2023). Chatgpt and how ai disrupts industries. Harvard Business Review. Analysis of AI's practical impact across global sectors.
                                                          Mollick, E. and Mollick, L. (2024). Co-Intelligence: Living and Working with AI. Penguin Random House. Practical guide to human-AI collaboration.
                                                          MongoDB, Inc. (2025). Mongodb manual. MongoDB, Inc. https://www.mongodb.com/docs/.
                                                          Morris, K. (2021). Infrastructure as Code: Dynamic Systems for the Cloud Age. O'Reilly Media, 2nd edition.
                                                          Murphy, K. P. (2012). Machine Learning: A Probabilistic Perspective. MIT Press.
                                                          Möttönen, M. and Vartiainen, J. (2023). Quantum Computing: From Qubits to Quantum Machines. Springer.
                                                          Müller, V. C. (2021). Ethics of Artificial Intelligence and Robotics. Cambridge University Press.
                                                          National Institute of Standards and Technology (2020). Security and privacy controls for information systems and organizations. Technical Report NIST SP 800-53 Rev. 5, National Institute of Standards and Technology, Gaithersburg, MD. Disponible en: https://csrc.nist.gov/publications/detail/sp/800-53/rev-5/final.
                                                          Navarro, G. (2016). Compact Data Structures. Cambridge University Press.
                                                          Newman, S. (2021). Building Microservices: Designing Fine-Grained Systems. O'Reilly Media, 2nd edition.
                                                          Ng, A. (2019). AI for everyone. Technical report, DeepLearning.AI. Continuously updated online course, available on Coursera.
                                                          Nielsen, M. A. and Chuang, I. L. (2010). Quantum Computation and Quantum Information. Cambridge University Press.
                                                          Noble, J. (2012). Programming Interactivity: A Designer's Guide to Processing, Arduino, and OpenFrameworks. O'Reilly Media, 2nd edition.
                                                          Norman, D. (2013). The Design of Everyday Things: Revised and Expanded Edition. Basic Books, 2nd edition.
                                                          of Cyberspace Studies, C. A. (2024). Ai governance and ethics in china. Technical report, Cyberspace Administration of China. Official Chinese perspective on AI governance and ethical standards.
                                                          Okasaki, C. (1999). Purely Functional Data Structures. Cambridge University Press.
                                                          OpenAI (2024). Best practices for prompt engineering. Updated official prompt engineering guidelines from OpenAI.
                                                          Özsu, M. T. and Valduriez, P. (2020). Principles of Distributed Database Systems. Springer, 4th edition.
                                                          Pacheco, P. S. and Malensek, M. (2021). An Introduction to Parallel Programming. Morgan Kaufmann, 2nd edition.
                                                          Parent, R. (2012). Computer Animation: Algorithms and Techniques. Morgan Kaufmann, 3rd edition.
                                                          Patterson, D. A. and Hennessy, J. L. (2020). Computer Organization and Design RISC-V Edition: The Hardware Software Interface. Morgan Kaufmann, 2nd edition.
                                                          Pavis, P. (1998). Dictionary of the Theatre: Terms, Concepts, and Analysis. University of Toronto Press.
                                                          Peterson, L. L. and Davie, B. S. (2022). Computer Networks: A Systems Approach. Morgan Kaufmann, 6th edition.
                                                          Pevzner, P. A. (2000). Computational Molecular Biology: an Algorithmic Approach. The MIT Press, Cambridge, Massachusetts.
                                                          Pfleeger, C. P., Pfleeger, S. L., and Margulies, J. (2015). Security in Computing. Prentice Hall, 5th edition.
                                                          Preskill, J. (2018). Lecture notes on quantum computation. Curso Ph219/CS219, California Institute of Technology. Material disponible en línea. La URL original http://theory.caltech.edu/~preskill/ph219/ no está operativa (febrero 2026). Se recomienda buscar la versión actual en el sitio web del autor.
                                                          Pressman, R. S. and Maxim, B. (2014). Software Engineering: A Practitioner's Approach. McGraw-Hill, 8th edition.
                                                          Pressman, R. S. and Maxim, B. (2019). Software Engineering: A Practitioner's Approach. McGraw-Hill Education, 9th edition.
                                                          Prince, S. J. D. (2012). Computer Vision: Models, Learning, and Inference. Cambridge University Press.
                                                          Prompt Engineering Institute (2024). Prompt engineering guide. https://www.promptingguide.ai/. Recurso integral de ingeniería de prompts actualizado continuamente. Accedido: 15 de enero de 2024.
                                                          Psaltis, A. (2017). Streaming Data: Understanding the real-time pipeline. Manning Publications.
                                                          Quinn, M. J. (2019). Ethics for the Information Age. Pearson, 8th edition.
                                                          R, D., S.R, E., A, K., and G, M. (1998). Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press.
                                                          Ramakrishnan, R. and Gehrke, J. (2002). Database Management Systems. McGraw-Hill, 3rd edition.
                                                          Ramakrishnan, R. and Gehrke, J. (2003). Database Management Systems. McGraw-Hill, 3rd edition.
                                                          Richards, M. and Ford, N. (2020). Fundamentals of Software Architecture: An Engineering Approach. O'Reilly Media, 1st edition.
                                                          Robbins, A. and Beebe, N. H. (2005). Classic Shell Scripting. O'Reilly Media, Sebastopol, CA, 1st edition.
                                                          Robbins, S. (2004). Comportamiento Organizacional. México,Pearson Educación.
                                                          Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B. (2022). High-resolution image synthesis with latent diffusion models. CVPR.
                                                          Rosen, K. H. (2019). Discrete Mathematics and Its Applications. McGraw-Hill Education, 8th edition.
                                                          Ross, S. M. (2014). A First Course in Probability. Pearson.
                                                          Russell, S. and Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson, 4th edition.
                                                          Russell, S. and Norvig, P. (2021). Artificial Intelligence: A Modern Approach. Pearson, 4th edition.
                                                          Sadalage, P. J. and Fowler, M. (2012). NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence. Addison-Wesley.
                                                          Samet, H. (2006). Foundations of Multidimensional and Metric Data Structures. Elsevier/Morgan Kaufmann.
                                                          Scheinerman, E. A. (2012). Mathematics: A Discrete Introduction. Cengage Learning, 3rd edition.
                                                          Schuld, M. and Petruccione, F. (2021). Machine Learning with Quantum Computers. Springer, Cham, Switzerland, 2nd edition. Comprehensive introduction to quantum machine learning algorithms and implementations.
                                                          Sedgewick, R. and Wayne, K. (2011). Algorithms. Addison-Wesley, 4th edition.
                                                          Serway, R. A. and Jewett, J. W. (2018). Physics for Scientists and Engineers with Modern Physics. Cengage Learning, 10th edition.
                                                          Setubal, J. C. and Meidanis, J. (1997). Introduction to computational molecular biology. Boston: PWS Publishing Company.
                                                          Shakelford, R., Cross, J. H., Davies, G., Impagliazzo, J., Kamali, R., LeBlanc, R., Lunt, B., McGettrick, A., Sloan, R., and Topi, H. (2005). Computing curricula 2005. Technical report, ACM/IEEE.
                                                          Shneiderman, B. (2022). Human-Centered AI. Oxford University Press, 1st edition.
                                                          Siegwart, R., Nourbakhsh, I. R., and Scaramuzza, D. (2011). Introduction to Autonomous Mobile Robots. MIT Press, 2nd edition.
                                                          Sikorski, M. and Honig, A. (2012). Practical Malware Analysis: The Hands-On Guide to Dissecting Malicious Software. No Starch Press, San Francisco, CA.
                                                          Silberschatz, A., Galvin, P. B., and Gagne, G. (2018). Operating System Concepts. Wiley, 10th edition.
                                                          Silberschatz, A., Korth, H. F., and Sudarshan, S. (2019). Database System Concepts. McGraw-Hill, 7th edition.
                                                          Sipser, M. (2012). Introduction to the Theory of Computation. Cengage Learning, 3rd edition.
                                                          Skiena, S. S. (2020). The Algorithm Design Manual. Springer, 3rd edition.
                                                          Soars, L. and John (2002a). American Headway N 1 Student Book. Editorial Oxford.
                                                          Soars, L. and John (2002b). American Headway N 2 Student Book. Editorial Oxford.
                                                          Soars, L. and John (2002c). American Headway N 3 Student Book. Editorial Oxford.
                                                          Soars, L. and John (2002d). American Headway N 3 Teachers Book. Editorial Oxford.
                                                          Soars, L. and John (2002e). American Headway N 3 Work Book. Editorial Oxford.
                                                          Society, I. C. (2021). Prácticas Profesionales en Computación: Ética y Gestión. IEEE Press. Manual de buenas prácticas para entornos laborales en TI.
                                                          Sohl-Dickstein, J., Song, Y., and Ermon, S. (2023). Diffusion Models: A Comprehensive Practical Guide. AI Press.
                                                          Soldan, D., Aylor, J., Clements, A., Engel, G., Hoelzeman, R., Hughes, E. A., Hughes, J. L., Impagliazzo, J., Jaeger, R. C., Klenke, R., Lyon, D. A., McGettrick, A., Nelson, V. P., Neebel, D. J., Page, I., Peterson, G. D., Ranganathan, N., Sloan, R., Srimani, P. K., Theys, M. D., Wolf, W., and Varanasi, M. (2016). Computer engineering curricula 2016. Technical report, ACM and IEEE-CS.
                                                          Sommerville, I. (2015). Software Engineering. Pearson, 10th edition.
                                                          Stair, R. and Reynolds, G. (2017). Principles of Information Systems. Cengage Learning, 13th edition.
                                                          Stallings, W. (2015). Computer Organization and Architecture: Designing for Performance. Pearson, 10th edition.
                                                          Stallings, W. (2017). Operating Systems: Internals and Design Principles. Pearson, 9th edition.
                                                          Stallings, W. (2022). Cryptography and Network Security: Principles and Practice. Pearson, 8th edition.
                                                          Stanislavski, C. (1936). An Actor Prepares. Theatre Arts Books.
                                                          Sterling, T., Brodowicz, M., and Anderson, M. (2024). High Performance Computing: Modern Systems and Practices. Morgan Kaufmann, 2nd edition.
                                                          Stewart, J. (2015). Calculus: Early Transcendentals. Cengage Learning.
                                                          Strang, G. (2016). Introduction to Linear Algebra. Wellesley-Cambridge Press.
                                                          Stroustrup, B. (2013). The C++ Programming Language. Addison-Wesley Professional, Upper Saddle River, NJ, 4th edition.
                                                          Stroustrup, B. (2022). A Tour of C++. Addison-Wesley Professional, Boston, MA, 3rd edition.
                                                          Sutton, R. S. and Barto, A. G. (2018). Reinforcement Learning: An Introduction. MIT Press, 2nd edition.
                                                          Szeliski, R. (2022). Computer Vision: Algorithms and Applications. Springer, 2nd edition.
                                                          Tanenbaum, A. S. and Austin, T. (2012). Structured Computer Organization. Pearson, 6th edition.
                                                          Tanenbaum, A. S. and Bos, H. (2014). Modern Operating Systems. Pearson, 4th edition.
                                                          Tanenbaum, A. S., Feamster, N., and Wetherall, D. J. (2021). Computer Networks. Pearson, 6th edition.
                                                          Tavani, H. T. (2013). Ethics and Technology: Controversies, Questions, and Strategies for Ethical Computing. Wiley, Hoboken, NJ, 4th edition.
                                                          Taylor, J. R. (2005). Classical Mechanics. University Science Books.
                                                          Team, G. A. Q. (2019). Quantum supremacy using a programmable superconducting processor. Nature, 574.
                                                          Team, I. Q. (2023). Qiskit Textbook. IBM.
                                                          Tencent AI Lab (2023). Responsible ai practices in chinese tech industry. Technical report, Tencent AI Lab. Industry perspective on AI ethics from leading Chinese tech company.
                                                          The Joint ACM/AIS IS2020 Task Force (2020). A competency model for undergraduate programs in information systems. Technical report, ACM Press and AIS Press.
                                                          Thrun, S., Burgard, W., and Fox, D. (2005). Probabilistic Robotics. MIT Press.
                                                          Tipler, P. A. and Mosca, G. (2007). Physics for Scientists and Engineers. W. H. Freeman and Company, 6th edition.
                                                          Traina Jr, C., Traina, A. J. M., Seeger, B., and Faloutsos, C. (2000). Slim-trees: High performance metric trees minimizing overlap between nodes. In Advances in Database Technology - EDBT 2000. Springer.
                                                          Tunstall, L., von Werra, L., and Wolf, T. (2022). Natural Language Processing with Transformers. O'Reilly Media.
                                                          UNESCO (2023). AI and education: Guidance for policy-makers. Technical report, UNESCO. Latest guidance on AI literacy and ethical implementation in education.
                                                          Union, E. (2024). AI Act: Regulatory framework. Technical report, European Commission. Comprehensive AI regulation framework effective 2024.
                                                          Valacich, J. and Schneider, C. (2021). Information Systems Today: Managing in the Digital World. Pearson, 9th edition.
                                                          van Steen, M. and Tanenbaum, A. S. (2023). Distributed Systems. Maarten van Steen, 4th edition.
                                                          Vandevoorde, D., Josuttis, N. M., and Gregor, D. (2017a). C++ Templates: The Complete Guide. Addison-Wesley Professional, Upper Saddle River, NJ, 2nd edition.
                                                          Vandevoorde, D., Josuttis, N. M., and Gregor, D. (2017b). C++ Templates: The Complete Guide. Addison-Wesley Professional, Upper Saddle River, NJ, 2nd edition.
                                                          Vandevoorde, D., Josuttis, N. M., and Gregor, D. (2018). C++ Templates: The Complete Guide. Addison-Wesley Professional.
                                                          Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A., Kaiser, L., and Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30.
                                                          Velleman, D. J. (2019). How to Prove It: A Structured Approach. Cambridge University Press, 3rd edition.
                                                          Voigt, P. and von dem Bussche, A. (2018). The EU General Data Protection Regulation (GDPR): A Practical Guide. Springer.
                                                          White, J. et al. (2023). A prompt pattern catalog to enhance prompt engineering with chatgpt. Peer-reviewed research on prompt engineering patterns.
                                                          White, T. (2015). Hadoop: The Definitive Guide. O'Reilly Media, 4th edition.
                                                          Wiegers, K. and Beatty, J. (2013). Software Requirements. Microsoft Press, 3rd edition.
                                                          Wigdor, D. and Wixon, D. (2011). Brave NUI World: Designing Natural User Interfaces for Touch and Gesture. Morgan Kaufmann.
                                                          Williams, A. (2019). C++ Concurrency in Action. Manning Publications, Shelter Island, NY, 2nd edition.
                                                          Young, H. D. and Freedman, R. A. (2015). Sears and Zemansky's University Physics with Modern Physics. Pearson Education, 14th edition.
                                                          Young, H. D. and Freedman, R. A. (2018). University Physics with Modern Physics. Pearson.
                                                          Zelle, J. M. (2010). Python Programming: An Introduction to Computer Science. Franklin, Beedle & Associates Inc, 2nd edition.
                                                          Zezula, P., Amato, G., Dohnal, V., and Batko, M. (2007). Similarity Search: The Metric Space Approach. Springer.thebibliography

                                                          Spotted a typo, an outdated course, a broken link, or have a suggestion? Let us know.

                                                          Scan to open on your phone