MAHE Manipal University
Artificial Intelligence & Machine Learning
MAHE Manipal University
₹2.2L – ₹2.2L
Total Fees
2 Years
Duration
ONLINE
Mode
★ 4.0
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About This Program at MAHE Manipal University
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Course Curriculum
| Semester 1 | Semester 2 | Semester 3 | Semester 4 |
|---|---|---|---|
| Programming Fundamentals: Introduction to programming concepts using languages like Python and Java, focusing on problem-solving and algorithmic thinking. | Object-Oriented Programming & Software Engineering: Principles of object-oriented design, software development life cycle, and best practices in coding. | Deep Learning & Neural Networks: Study of artificial neural networks, convolutional neural networks, recurrent neural networks, and deep learning architectures. | Advanced Machine Learning Techniques: Reinforcement learning, ensemble learning, and optimization algorithms for complex problem-solving. |
| Data Structures and Algorithms: Study of fundamental data structures, algorithm design, and computational complexity to solve real-world problems efficiently. | Machine Learning Basics: Introduction to supervised, unsupervised, and reinforcement learning algorithms, including regression, classification, clustering, and dimensionality reduction. | Natural Language Processing (NLP): Techniques for text processing, sentiment analysis, language modeling, and AI-driven communication systems. | AI Ethics, Security, and Governance: Ethical AI practices, data privacy, responsible AI deployment, and regulatory compliance. |
| Database Management Systems: Introduction to database concepts, SQL, data modeling, and database design principles. | Data Analytics & Visualization: Techniques for analyzing large datasets, interpreting patterns, and visualizing results using tools like Tableau and Python libraries. | Computer Vision & Image Processing: Algorithms and tools for image recognition, object detection, and visual data analysis. | AI in Industry Applications: AI applications in healthcare, finance, e-commerce, manufacturing, and smart systems. |
| Computer Architecture & Operating Systems: Basics of hardware, operating systems, memory management, and process scheduling. | Artificial Intelligence Fundamentals: Basics of AI, intelligent agents, problem-solving, search algorithms, and knowledge representation. | Big Data & Cloud Computing for AI: Handling large-scale data, distributed computing, and deploying AI models on cloud platforms. | Entrepreneurship and Innovation in AI: Developing AI-based solutions, startup strategies, and business models in technology-driven industries. |
| Mathematics for Computing: Linear algebra, probability, and discrete mathematics applicable to AI and ML. | Applied Statistics & Probability: Statistical methods and probability theory for data analysis and machine learning. | AI & ML Project Work: Practical project to implement AI/ML models for real-world applications. | Capstone Project / Dissertation: Comprehensive project where students design, implement, and present an AI or ML solution, demonstrating their mastery of concepts and practical skills. |
Learning Outcomes
What you will achieve after completing this program
Graduates develop a deep understanding of both foundational computer science principles and advanced AI and machine learning concepts. They gain expertise in algorithms, neural networks, deep learning, natural language processing, and computer vision, enabling them to design, develop, and optimize AI systems for diverse applications. This knowledge equips students to solve complex technical problems and innovate in AI-driven environments.
The program emphasizes data-driven decision-making, equipping graduates to analyze large and complex datasets, extract meaningful insights, and apply predictive and prescriptive analytics. By mastering data visualization, statistical modeling, and machine learning techniques, students can support strategic decisions, optimize processes, and enhance business performance across sectors.
Students gain practical experience through projects, lab exercises, and real-world applications of AI and ML technologies. They become adept at programming, deploying models on cloud platforms, developing AI solutions, and integrating AI into existing business or technological systems. This hands-on expertise ensures graduates are job-ready and capable of contributing to live AI projects immediately.
The curriculum nurtures critical thinking, logical reasoning, and problem-solving skills. Graduates learn to approach complex challenges systematically, evaluate multiple solutions, and implement optimal AI-driven strategies. This ability to analyze, innovate, and optimize positions students as valuable contributors in research, product development, and technology strategy roles.
Eligibility Criteria
Who Can Apply
Bachelor’s degree in Computer Science, Information Technology, Electronics, or related fields from a recognized university.
Graduates from other disciplines may be considered if they possess basic programming knowledge and mathematical aptitude.
Minimum 50% aggregate marks in graduation (45% for reserved category candidates).
Required Documents
10th & 12th Marksheets
Graduation Certificate
Government ID Proof
Passport Size Photo
Finance Your Education
Total Program Fee
₹2.2L
≈ ₹55K per semester
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Scholarship
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Fee Structure
| Total Program Fee | ₹2.2L – ₹2.2L |
| Semester Fee | ₹55K |
| Duration | 2 Years |
| Mode | ONLINE |
| Exam Fee | Included |
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Artificial Intelligence & Machine Learning
MAHE Manipal University