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Comprehensive Course Structure

The Data Science program at Adani University Ahmedabad spans eight semesters, with a carefully designed curriculum that balances theoretical foundations, practical applications, and real-world project exposure. Below is a detailed table outlining all courses offered across the program:

Detailed Course Descriptions for Departmental Electives

Departmental elective courses are designed to deepen students' expertise in specialized areas of data science. These courses offer a blend of theory and practice, often incorporating real-world datasets and industry projects.

• Machine Learning Fundamentals (CSE-301): This course introduces students to foundational concepts in machine learning including supervised and unsupervised learning algorithms, model selection, and validation techniques. Students will implement algorithms using Python and Scikit-learn.
• Deep Learning and Neural Networks (CSE-302): Focuses on neural network architectures such as CNNs, RNNs, LSTMs, and Transformers. Students will gain hands-on experience with frameworks like TensorFlow and PyTorch.
• Data Visualization and Storytelling (CSE-303): Emphasizes the importance of effective data communication through interactive dashboards, visualizations, and storytelling techniques. Tools such as Tableau, Power BI, and D3.js are introduced.
• Big Data Technologies (CSE-401): Explores distributed computing frameworks like Hadoop and Spark for processing large-scale datasets. Students will learn to design and deploy scalable data pipelines.
• Natural Language Processing (CSE-402): Covers text preprocessing, sentiment analysis, language modeling, and transformer-based architectures. Students will build applications for chatbots, summarization, and question answering systems.
• Computer Vision and Image Processing (CSE-403): Introduces image processing techniques, object detection, segmentation, and classification using deep learning models. Practical applications include medical imaging and autonomous vehicles.
• Reinforcement Learning (CSE-501): Explores decision-making processes in dynamic environments using reinforcement learning algorithms. Applications include robotics, game playing, and recommendation systems.
• Advanced Data Mining Techniques (CSE-502): Focuses on association rule mining, clustering, anomaly detection, and graph analytics. Students will analyze large datasets to discover hidden patterns and relationships.
• Privacy-Preserving Analytics (CSE-503): Addresses ethical and legal considerations in data usage, including differential privacy, federated learning, and secure multi-party computation.
• Applied Machine Learning in Industry (CSE-601): Provides students with insights into how machine learning is applied in real-world business contexts. Guest speakers from industry share case studies and best practices.

Project-Based Learning Philosophy

The Data Science program at Adani University Ahmedabad emphasizes project-based learning to ensure that students gain practical experience and develop problem-solving skills. Projects are designed to simulate real-world challenges and encourage innovation and collaboration.

Mini-projects begin in the third semester, where students work on small-scale datasets under faculty supervision. These projects are assessed based on technical competency, clarity of presentation, and ability to communicate findings effectively.

The final-year capstone project or thesis is a significant undertaking that spans the entire seventh and eighth semesters. Students select their topics in consultation with faculty mentors, who guide them through literature review, methodology design, implementation, and analysis. The project culminates in a public presentation and defense before an academic committee.

Evaluation criteria for projects include:

• Technical Depth and Innovation
• Data Quality and Source Credibility
• Model Performance and Validation
• Documentation and Code Readability
• Presentation Skills and Communication