M.Tech. In Machine Learning and Data Science Syllabus - SRM Valliammai Engineering college (VEC), Kanchipuram

  • Years 2 Years
  • Type Course Post Graduate
  • stream Engineering
  • Delivery Mode
Written By universitykart team | Last updated date Jul, 07, 2024

The Master of Technology (M.Tech.) Machine Learning and Data Science syllabus at SRM Valliammai Engineering college (VEC), Kanchipuram is designed to provide overall knowledge to the students with a strong foundation. Master of Technology (M.Tech.) Machine Learning and Data Science faculty at SRM Valliammai Engineering college (VEC) specially focus on in-depth learning to relevant subjects. At first semester syllabus of Master of Technology (M.Tech.) Machine Learning and Data Science at SRM Valliammai Engineering college (VEC), students learn the basics of programme. A strong foundation is very important for comprehensive learning. Master of Technology (M.Tech.) Machine Learning and Data Science syllabus at SRM Valliammai Engineering college (VEC), Kanchipuram maintains a balance between theoretical knowledge and practical knowledge.

Master of Technology (M.Tech.) Machine Learning and Data Science first year students at SRM Valliammai Engineering college (VEC) are introduced with core subjects. Then they are encouraged to explore other area for a broader perspective. SRM Valliammai Engineering college (VEC), Kanchipuram also provides practical training sessions, workshops, projects, and case studies to enhance student skills. Master of Technology (M.Tech.) Machine Learning and Data Science syllabus at SRM Valliammai Engineering college (VEC), Kanchipuram is also frequently updated to give industry relevant training and knowledge to students. SRM Valliammai Engineering college (VEC) strives to provide a nurturing environment where students can learn new skills. The hands-on training sessions at SRM Valliammai Engineering college (VEC) enable Master of Technology (M.Tech.) Machine Learning and Data Science students to apply knowledge and skills in a controlled environment and get required experience.

According to syllabus of Master of Technology (M.Tech.) Machine Learning and Data Science progress, students learn advanced topics and complex concepts. The Master of Technology (M.Tech.) Machine Learning and Data Science curriculum at SRM Valliammai Engineering college (VEC), Kanchipuram mainly focuses on analytical and critical thinking. As the Master of Technology (M.Tech.) Machine Learning and Data Science course unfolds, students develop several important skills that increases their employability. As per syllabus of Master of Technology (M.Tech.) Machine Learning and Data Science at SRM Valliammai Engineering college (VEC) also includes real-life projects and internship programs. It helps students critical thinking and gives them real-world experience.

Master of Technology (M.Tech.) Machine Learning and Data Science curriculum at SRM Valliammai Engineering college (VEC) includes group discussions, guest lectures, case studies, and skill development workshops to enhance the learning experience. The Master of Technology (M.Tech.) Machine Learning and Data Science syllabus at SRM Valliammai Engineering college (VEC) aims to create well-rounded professionals equipped with the necessary skills and knowledge to succeed in their chosen fields.

Additional curriculum at SRM Valliammai Engineering college (VEC)

  1. Workshops and Seminars - Regular sessions with industry experts help Master of Technology (M.Tech.) Machine Learning and Data Science students at SRM Valliammai Engineering college (VEC) to stay updated with current trends.
  2. Group Projects - Collaborative projects according to SRM Valliammai Engineering college (VEC) syllabus develop teamwork and problem-solving skills.
  3. Case Studies - Master of Technology (M.Tech.) Machine Learning and Data Science syllabus offers analysis of real-world scenarios to apply theoretical knowledge.
  4. Extracurricular Activities - SRM Valliammai Engineering college (VEC) offers several activities like sports, clubs, societies, etc. to encourage overall development.

Note: Given below syllabus is based on the available web sources. Please verify with the SRM Valliammai Engineering college (VEC), Kanchipuram for latest Master of Technology (M.Tech.) Machine Learning and Data Science curriculum.

Syllabus and subjects in M.Tech. Machine Learning and Data Science

The M.Tech. in Machine Learning and Data Science syllabus is a comprehensive program designed to equip students with the essential knowledge and skills required to excel in the rapidly evolving fields of machine learning and data science. The curriculum typically encompasses a wide range of subjects, including but not limited to, statistics, linear algebra, data preprocessing, machine learning algorithms, deep learning, natural language processing, computer vision, big data analytics, and ethical considerations in data science. Students can expect to engage in hands-on projects, collaborate on real-world data problems, and gain proficiency in programming languages such as Python and R. Additionally, coursework often delves into advanced topics such as reinforcement learning, generative adversarial networks, and distributed computing. By the end of the program, graduates are not only well-versed in the latest technological advancements but also possess a deep understanding of the ethical and societal implications of data-driven decision-making, positioning them for successful careers in academia, industry, or research.


1st Year OR 1st & 2nd Semester Syllabus of Master of Technology (M.Tech.) Machine Learning and Data Science

S.noSubjects
1Python For Data Science
2Machine Learning
3Database And SQL
4Mathematical Foundation
5Statistical Methods For Decision Making                                                                          
6Data Visualization                                                                        

2nd Year OR 3rd & 4th Semester Syllabus of Master of Technology (M.Tech.) Machine Learning and Data Science

S.NoSubjects
1Classification Algorithms                                                         
2Unsupervised Algorithms                                                                                                         
3Hadoop
4Text Analytics - Basics
5Thesis
6Project

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