Jaipur National University
MCA at Jaipur National University
The MCA program at JNU is a blend of theoretical foundations and practical applications in computer science, AI, and ML. Students learn to develop intelligent systems capable of solving complex real-world problems using advanced technologies. This program is ideal for aspirants passionate about harnessing the potential of AI and ML to shape the future.
MCA Course Details
| Parameter | Details |
|---|---|
| University Name | Jaipur National University |
| Course Name | MCA Specialization in Artificial Intelligence and Machine Learning |
| Duration | 2 Years |
| Course Fee | 1,27,800 Per Year |
| Eligibility | - Bachelor's degree in any discipline - At least 50% marks in aggregate - Mathematics as a subject at 10+2 or graduation level |
Eligibility Criteria for MCA
To enroll in the MCA program with a specialization in AI and ML, candidates must meet the following eligibility requirements:
- A Bachelor's degree in any discipline with at least 50% marks in aggregate.
- Mathematics as a subject at either the 10+2 level or during graduation.
Career Opportunities after MCA
Graduates of this program can explore diverse career paths in the rapidly growing field of AI and ML. Some potential roles include:
- AI Engineer
- Machine Learning Specialist
- Data Scientist
- Business Intelligence Analyst
- AI Research Scientist
- Big Data Engineer
Top Recruiters: Leading companies in technology, healthcare, finance, and e-commerce are actively hiring AI and ML professionals, such as:
- Microsoft
- Amazon
- Infosys
- TCS
- Wipro
MCA Course Outline
The MCA program at JNU offers a comprehensive curriculum, structured to balance theory and practice. Below is a semester-wise breakdown of the course:
First Year
| Semester | Subjects |
|---|---|
| Semester 1 | - Programming in Python - Advanced Mathematics for AI - Data Structures and Algorithms - Computer Organization and Architecture - AI Fundamentals - Lab: Python Programming |
| Semester 2 | - Machine Learning Basics - Database Management Systems - Operating Systems - Software Engineering - Probability and Statistics - Lab: Machine Learning Models |
Second Year
| Semester | Subjects |
|---|---|
| Semester 3 | - Deep Learning - Natural Language Processing - Big Data Analytics - Internet of Things (IoT) - Elective I (Choose from Cloud Computing, Cybersecurity, or Blockchain) - Lab: Deep Learning and NLP |
| Semester 4 | - Advanced AI Topics (Reinforcement Learning, Computer Vision) - AI in Industry Applications - Project Management - Internship/Capstone Project - Lab: AI Industry Solutions |
Learning Outcomes
- Technical Proficiency: Develop expertise in programming languages like Python, R, and tools like TensorFlow, Keras, and PyTorch.
- Problem-solving Skills: Analyze complex problems and create innovative AI/ML-driven solutions.
- Industry-ready Skills: Gain experience through practical labs, internships, and real-world projects.
- Research-oriented Approach: Build a foundation for pursuing research or higher studies in AI and ML.
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