Rayat Shikshan Sanstha's
KARMAVEER BHAURAO PATIL COLLEGE,
VASHI. NAVI MUMBAI
(Autonomous)
Name of the Faculty: Science and Technology
Name of the Program : B.Sc. AIML
Program Outcomes (POs) |
| PO-1 | Disciplinary Knowledge | Understand the basic concepts, fundamental principles, theoretical formulations and experimental findings and the scientific theories related to Physics, Chemistry, Mathematics, Microbiology, Computer Science,Biotechnology, Information Technology and its other fields related to the program. |
| PO-2 | Communication Skills | Develop various communication skills such as reading, listening and speaking skills to express ideas and views clearly and effectively. |
| PO-3 | Critical Thinking | Propose novel ideas in explaining the scientific data, facts and figures related to science and technology. |
| PO-4 | Analytical Reasoning and Problem Solving | Hypothesize, analyze, formulate and interpret the data systematically and solve theoretical and numerical problems in the diverse areas of science and technology. |
| PO-5 | Sense of Inquiry | Curiously ask relevant questions for better understanding of fundamental concepts and principles, scientific theories and applications related to the study. |
| PO-6 | Use of Modern Tools | Operate modern tools, equipment, instruments and laboratory techniques to perform the experiments and write the programs in different languages (software). |
| PO-7 | Research Skills | Understand how to design, collect, analyze, interpret and evaluate information/data that is relevant to science and technology. |
| PO-8 | Application of Knowledge | Develop a scientific outlook and apply the knowledge with respect to the subject. |
| PO-9 | Ethical Awareness | Imbibe ethical, moral and social values and exercise it in day to day life. |
| PO-10 | Teamwork | Work collectively and participate to take initiative for various field-based situations related to science, technology and society at large. |
| PO-11 | Environment and Sustainability | Create social awareness about the environment and develop sustainability for betterment of the future. |
| PO-12 | Lifelong Learning | Ability of self-driven to explore, learn and gain knowledge and new skills to improve the quality of life and sense of self-worth by paying attention to the ideas and goals throughout the life. |
Rayat Shikshan Sanstha's
KARMAVEER BHAURAO PATIL COLLEGE, VASHI.
NAVI MUMBAI (Autonomous)
Department of Artificial Intelligence and Machine Learning
Program Specific Outcomes(PSO) |
| PSO-1 | Apply theoretical knowledge to develop intelligent systems solving
domain-specific problems. | - |
| PSO-2 | Analyse data and machine learning models to derive insights and actionable
decisions. | - |
| PSO-3 | Engage in project-based learning that integrates research, experimentation, and innovation. | - |
| PSO-4 | Collaborate in multidisciplinary teams to design scalable and ethical AI/ML systems. | - |
| Title of Specific Program : B.Sc. AIML |
| Course Outcome (CO) |
| Course Code | Course Title | Course Outcome |
| F.Y. SEM I |
| AIML101 | Python Programming for AI & ML | CO-1 :Understand basic programming constructs in Python
CO-2 : Write Python programs using decision-making and loops
CO-3 :Implement functions and built-in data structures
CO-4 :Apply Python programming to simple AI/ML-oriented problems |
| AIML102 | Fundamentals of Computer Systems | CO-1: Explain the basic concepts of computer science and components of a computer system.
CO-2: Apply logical reasoning and algorithmic thinking to solve simple problems.
CO-3: Describe data representation techniques and basic programming concepts.
CO-4: Identify different types of software, operating systems, and their functions.
CO-5: Discuss emerging trends and applications in computer science. |
| AIML104 | Basic Statistics & Probability | CO-1: Understand and explain basic statistical terminology and concepts.
CO-2 : Organize and summarize data using descriptive statistics.
CO-3: Apply probability concepts to simple real-world problems.
CO-4: Understand probability distributions and random variables.
CO-5: Interpret statistical results for data-driven decision-making. |
| AIML151 | Advanced Python Programming for AI & ML | CO-1: Explain advanced Python programming concepts including OOP principles, decorators, generators, context
managers, and exception handling.
CO-2: Analyze and apply advanced data structures (lists, tuples, sets, dictionaries, comprehensions) and functional
programming constructs (lambda, map, filter, reduce)..
CO-3: Illustrate the working of Python scientific computing libraries such as NumPy and Pandas for numerical and
data analysis tasks.
CO-4: Interpret data visualization techniques using Matplotlib and Seaborn for exploratory data analysis. |
| AIML152 | Descriptive Statistics for Data Science | CO-1 : Identify different types of data used in data science
CO-2 :Organize and visualize datasets effectively
CO-3 : Compute and interpret measures of central tendency
CO-4 :Analyze data variability and distribution shape |
| AIML154 | Data Structures & Algorithms | CO-1: Understand basic concepts of data structures and algorithms.
CO-2: Implement simple linear data structures such as arrays, linked lists, stacks, and queues.
CO-3: Apply basic searching and sorting techniques.
CO-4: Analyze basic time and space complexity of algorithms. |
