विज्ञान शास्त्र प्रौद्योगिकी और परिशोधन संगठन, हैदराबाद
విజ్ఞాన శాస్త్ర సాంకేతిక పరిశోధనా సంస్థ, హైదరాబాద్
Dept. of Computer Science & Engineering
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Dept. of Computer Science & Engineering

  • Course Description
  • Course Structure
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Program Educational Objectives (PEOs)

PEO 1: Pursue a successful professional career in IT and IT-enabled industries.

PEO 2: Pursue lifelong learning in generating innovative engineering solutions using research and complex problem-solving skills.

PEO 3: Demonstrate professionalism, ethics, inter-personal skills and continuous learning to develop leadership qualities.

Program Specific Outcomes (PSOs)

PSO 1: DataScienc for Life: Ability to represent the knowledge and predicate logic and then transform the real-life information into a different representation.

PSO 2: AI Application Development: Design and Develop Deep Learning Models on the Cloud System using Cloud Services like Amazon Web Services, Microsoft Azure, Hadoop System, etc., to work on AI & ML for providing solutions to Geo-Socio-Economic problems.

Program Outcomes (POs)

Program Outcomes (POs), are attributes acquired by the student at the time of graduation. The POs given in below, ensure that the POs are aligned to the Graduate Attributes (GAs) specified by National Board of Accreditation (NBA). These attributes are measured at the time of Graduation.

PO 1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

PO 2: Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PO 3: Design/development of solutions:Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

PO 4: Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

PO 5: Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.

PO 6: The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.

PO 7: Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

PO 8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO 9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO 10: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

PO 11: Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one's own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

PO 12: Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

B.Tech. CSE - Artificial Intelligence (AI) & Machine learning (ML)

VFSTR has introduced a four-year B.Tech.CSE - Artificial Intelligence (AI) & Machinelearning (ML) from the academic year2020-21. AI & ML is a well-establishedspecialization of computer scienceconcerned with methods to designcomputers or machines as intelligent.

AIML provides applications that have an ability to learn through the experience without being explicitly Programd. ML enables applications to recognize patterns in the data in the same way as human brains do. It has become an integral part of our day to day lives and few of the widely used applications are Traffic Alerts, Social Media (Facebook, Twitter), Product Recommendations (Amazon, FlipKart), Virtual Personal Assistants (Siri, Google Assist), Directions in Google maps, Self-Driving Cars, Online Video Streaming (NetFlix). As per the recent reports, AI/ ML Engineer is the best job of 2019 due to the growing skill demand that attracts high salaries. AI/ ML professionals are getting an annual hike of 20-30% when compared to other skill areas. Starting such a program is a step towards fulfilling the high skill demand for AI/ ML professionals across the globe.

Career Opportunities
B.Tech. CSE - AIML prepares students for the below job roles.

  • Data Analyst
  • ML/AI Engineer
  • Machine Learning Architect
  • Data Scientist
  • Data Engineer
  • Business Intelligence Engineer
  • Research Scientist
  • Software Engineer/ Developer

  • I Year (R21 Regulation) I Semester
    Code Subject L T P C
    22MT103 Linear Algebra and Ordinary Differential Equations 3 2 0 4
    22PY105 Semiconductor Physics and Electromagnetics 2 0 2 3
    22EE101 Basic Electrical and Electronics Engineering 2 0 2 3
    22CS103 IT Workshop and Tools 0 2 4 3
    22TP103 Programming in C 2 0 4 4
    22EN102 English Proficiency and Communication Skills 0 0 2 1
    22TP101 Constitution of India 0 2 0 1
    22SA101 Physical Fitness, Sports & Games - I 0 0 3 1
      Total 9 6 17 20
                      
    I Year (R21 Regulation) II Semester
    Code Subject L T P C
    22MT105 Advanced Engineering Mathematics 3 2 0 4
    22MT107 Discrete Mathematical Structures 2 2 0 3
    22ME101 Engineering Graphics 2 0 2 3
    22TP104 Basic Coding Competency 0 1 3 2
    22EN104 Technical English Communication 2 0 2 3
    22CS104 Python Programming 2 0 2 3
    22SA102 Orientation Session 0 0 6 3
    22SA103 Physical Fitness, Sports & Games - II 0 0 3 1
      Total 11 5 18 22
                      
    II Year (R21 Regulation) I Semester
    Code Subject L T P C
    22ST203 Probability Theory and Statistics for Machine Learning 3 0 2 4
    22MS201 Management Science 2 2 0 3
    22TP202 Data Structures using Python 2 2 2 4
    22AM201 Artificial Intelligence 2 2 2 4
    22AM202 Digital Logic and Computer Organization 2 2 0 3
    22CS201 Database Management Systems 2 2 2 4
    22CT201 Environmental Studies 1 1 0 1
    22SA201 Life Skills-I 0 0 2 1
    NCC/ NSS/ SAC/ E-cell/ Student Mentoring/ Social activities/ Publication. 0 0 0 1
      Total 14 11 10 25
                      
    II Year (R22 Regulation) II Semester
    Code Subject L T P C
    22TP203 Advanced Coding Competency 0 0 2 1
    22TP204 Professional Communication 0 0 2 1
    22AM203 Design and Analysis of Algorithms using Python 2 2 2 4
    22AM204 Machine Learning 3 0 2 4
    22CS203 Object-Oriented Programming through JAVA 2 0 4 4
    22CS207 Operating Systems 2 0 2 3
    22SA202 Life Skills-II 0 0 2 1
    Open Elective – 1 3 0 0 3
      Total 12 2 16 21
    Minor / Honours - 1 3 0 2 4
      Total 15 2 18 25
                      
    III Year (R22 Regulation) I Semester
    Code Subject L T P C
    22TP301 Soft Skills Laboratory 0 0 2 1
    22AM301 Deep Learning 3 0 2 4
    22CS204 Computer Networks 3 0 2 4
    22DS203 Formal Languages and Automata Theory 2 2 0 3
    22AM302 Inter-Disciplinary Project – Phase I 0 0 2 0
    22AM303 Industry Interface Course 1 0 0 1
    Department Elective – 1 3 0 2 4
    Open Elective – 2 3 0 0 3
    NCC/ NSS/ SAC/ E-cell/ Student Mentoring/ Social activities/ Publication. 0 0 0 1
      Total 15 2 10 21
    Minor / Honours - 2 3 0 2 4
      Total 18 2 12 25
                      
    III Year (R22 Regulation) II Semester
    Code Subject L T P C
    22TP302 Quantitative Aptitude and Logical Reasoning 1 2 0 2
    22AM304 Fundamentals of Image Processing 2 0 2 3
    22AM305 Reinforcement Learning 2 2 0 3
    22CS303 Web Technologies 2 0 4 4
    22AM306 Inter-Disciplinary Project – Phase II 0 0 2 2
    Department Elective – 2 3 0 2 4
    Open Elective – 3 3 0 0 3
      Total 13 4 10 21
    Minor / Honours - 3 3 0 2 4
      Total 16 4 12 25
                      
    IV Year (R22 Regulation) I Semester
    Code Subject L T P C
    22AM401 Knowledge Representation and Reasoning 2 2 0 3
    22AM402 Text Mining 3 0 2 4
    22CS402 Big Data Analytics 3 0 2 4
    Department Elective – 3 3 0 2 4
    Open Elective – 4 3 0 2 4
      Total 14 2 8 19
    Minor / Honours - 4 3 0 2 4
      Total 17 2 10 23
                      
    IV Year (R22 Regulation) II Semester
    Code Subject L T P C
    22AM403 Internship/ Project work 0 2 22 12
    Total022212
    Minor / Honours - 5 0 2 6 4
    Total042816
                      
        L=Lecture;    T=Tutorial;    P=Practicals;    To=Total; C=Credits;

    Program Name B.Tech CSE - Artificial Intelligence and Machine Learning
    Level Under Graduation
    Program Specific Enquiries 0863-2344731
    Admission Enrollment and General Enquiries 0863-2344777, 1800-425-2529
    HoD Contact Number 9840850744