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MCA in Artificial Intelligence and Machine Learning is a postgraduate program in computer science that focuses on providing advanced knowledge and skills in the areas of artificial Intelligence & machine learning, computer systems, algorithms, and data analysis.

The Masters in AI and ML program is designed to prepare students for careers in the rapidly growing field of computer technology, and to provide a strong foundation in computer science theory and practice.

Eligibility

To enroll for MCA in AI and ML course, a candidate needs to pass with 45% aggregate marks in BCA or B.Sc. (Computer Science) or B.Sc. (Information Technology) or any Graduation

  • Duration
    2 Years
  • Fee (Per Semester)
    50,000/-
    Examinations Fee (Per Semester)
    1,500/-
    Registration Fee
    500/-
    Enrollment Fee
    1,000/-

 

Highlights

  • Objectives of MCA programme In AI & ML is to provide students with a comprehensive and well-rounded education in artificial Intelligence & machine learning that prepares them for successful career in the field and for lifelong learning and professional development. We aimed :
  • The program aims to provide students with a comprehensive understanding of the principles, theories, algorithms, and methodologies of AI and ML. Students gain knowledge of different AI techniques, ML algorithms, statistical models, and data analysis methods.
  • The MCA program ensures that students have a strong foundation in core computer science concepts. This includes knowledge of programming languages, data structures, algorithms, computer networks, databases, operating systems, and software engineering principles.
  • Students are trained in using state-of-the-art tools and technologies relevant to AI and ML. They gain hands-on experience with popular AI and ML frameworks, libraries, and software platforms. This includes proficiency in programming languages such as Python and R, as well as frameworks like TensorFlow, PyTorch, scikit-learn, and Apache Spark.
  • The program emphasizes practical application of AI and ML concepts. Students work on real-world projects and case studies to apply their knowledge to solve complex problems. They develop skills in data pre-processing, feature selection, model building, model evaluation, and result interpretation.
Program-objective

Curriculum Details

  • Analytics Programming Fundamental
  • MICRO–PROCESSORS AND ASSEMBLY LANGUAGE PROGRAMMING
  • DISCRETE MATHEMATICS STRUCTURE
  • SAS® Enterprise Guide® ANNOVA, Regression, and Logistic Regression
  • Application of Machine Learning Using SAS® Viya ®
  • COMPUTER APPLICATIONS – I
  • SAS Programming in Viya
  • ADVANCE PYTHON PROGRAMMING
  • ADVANCE PYTHON PROGRAMMING LAB

  • SAS® Visual Text Analytics in SAS® Viya
  • COMPUTER ORGANIZATION AND ARCHITECTURE
  • OBJECT ORIENTATED PROGRAMMING USING C++
  • NEURAL NETWORKS: ESSENTIALS
  • C++ PROGRAMMING LAB
  • Deep Learning Using ® Software
  • SEMINAR

  • ADVANCED CLOUD COMPUTING
  • ANALYSIS AND DESIGN OF ALGORITHM
  • Optimazation Concepts for Data Science and Artificial Intelligence
  • INFORMATION SECURITY LAB
  • Forecasting Using Model Studio in SAS® Viya® DATA SCIENCE WITH R
  • ANALYSIS AND DESIGN OF ALGORITHM LAB
  • DATA MINING AND WAREHOUSING
  • BIG DATA TECHNOLOGIES WITH PYTHON
  • SOFT COMPUTING
  • ENERGY AUDITING
  • SOLID AND HAZARDOUS WASTE MANAGEMENT
  • DIGITAL ELECTRONICS

  • Internship
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Program Outcomes (POs)

  • PO1

    Equip students with a strong foundation in various technical skills such as programming, database management, software development, and computer networking.

  • PO2

    Develop students' ability to think critically, solve complex problems, and make decisions using data-driven techniques.

  • PO3

    Exposed to the latest trends and advancements in the field of computer applications, giving them a competitive edge when entering the workforce.

  • PO4

    Pursue a wide range of careers in software development, IT consulting, data analysis, and other related fields.

  • PO5

    Opportunities for students to develop entrepreneurial skills and explore innovative

  • PO6

    Able to work effectively, individually and on teams, including diverse and multidisciplinary, to accomplish a common goal.

  • PO7

    Able to communicate effectively and develop self-confidence

  • PO8

    Able to understand of professional, ethical, legal, security and social issues and responsibilities.

  • PO9

    Develop ability to use current technologies, skills and models for computing practice..

Program Educational Objectives (PEO)

Excel in professional career and/or higher education by acquiring knowledge in mathematical, computing and engineering principles

Work with ethics and moral values in industry with constant growth in their future.

Exhibit innovativeness and participate in research work

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outcomes

Career Path

  • AI Engineer
  • ML Engineer
  • Data Scientist
  • Research Scientist
  • AI Consultant
  • Data Engineer
  • AI Product Manager
  • AI Entrepreneur
  • Academia and Research
  • Industry-Specific AI Role

FAQ

What is the difference between AI and ML?
Artificial Intelligence (AI) refers to the broader field of creating intelligent machines that can perform tasks that typically require human intelligence. Machine Learning (ML) is a subset of AI that focuses on algorithms and statistical models that enable machines to learn and make predictions or decisions without being explicitly programmed.
What are the prerequisites for an MCA in AI and ML?
Prerequisites may vary depending on the specific program, but typically a bachelor's degree in computer science or a related field is required. Some programs may also have prerequisites in mathematics, statistics, and programming. Additionally, having a solid foundation in computer science concepts and programming languages can be beneficial.
What courses are covered in an MCA program in AI and ML?
The courses offered may vary, but common subjects covered include AI fundamentals, ML algorithms, data mining, deep learning, natural language processing, computer vision, statistical modeling, data analytics, and software development. Additionally, there may be elective courses and project-based courses focused on practical applications of AI and ML
What kind of projects can I expect to work on during the program?
MCA programs often include project-based courses where students work on real-world problems in AI and ML. Projects can vary widely and may involve tasks such as image classification, sentiment analysis, recommendation systems, natural language understanding, or analyzing large datasets for insights. These projects provide hands-on experience and the opportunity to apply learned concepts.
Are there any internship opportunities during the program?
Many MCA programs collaborate with industry partners to provide internship opportunities. Internships allow students to gain practical experience by working on AI and ML projects in real-world settings. They provide exposure to industry practices, networking opportunities, and the chance to apply classroom knowledge in professional environments.
What career opportunities are available after completing an MCA in AI and ML?
Graduates can pursue various career paths such as AI engineer, ML engineer, data scientist, research scientist, AI consultant, data engineer, AI product manager, or academia as professors or researchers. The demand for AI and ML professionals is growing rapidly in industries like technology, healthcare, finance, e-commerce, and more.
Can I continue my education and pursue a Ph.D. after completing an MCA in AI and ML?
Yes, an MCA in AI and ML can be a stepping stone for pursuing a Ph.D. in a related field. It provides a strong foundation and research experience that can help in securing admission to Ph.D. programs. Ph.D. programs offer the opportunity to conduct advanced research, contribute to academia, and make significant contributions to the field of AI and ML.
How can I stay updated with the latest advancements in AI and ML?
The field of AI and ML is rapidly evolving. To stay updated, you can join professional AI and ML communities, attend conferences and workshops, read research papers, follow leading experts and organizations in the field, and participate in online courses or certifications. Continuous learning and engagement with the AI and ML community are crucial to stay abreast of the latest developments.

Campus
Nirwan University Jaipur

Near Bassi-Rajadhok Toll, Agra Road, Jaipur- 303305

City Office

21, Sahkar Marg, 1st Floor, Near 22 Godam Circle
Jaipur - 302019 Rajasthan
Campus

Nirwan University

Near Bassi-Rajadhok Toll, Village- Jhar, Agra Road, Jaipur - 303305 Rajasthan
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