- Course Description
- Course Structure
- Course Enquiry
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.
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 | |
Total | 0 | 2 | 22 | 12 | ||
Minor / Honours - 5 | 0 | 2 | 6 | 4 | ||
Total | 0 | 4 | 28 | 16 |
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 |