PGP in AI & Machine Learning Course Syllabus - Great Learning, Gurgaon

  • Years 1 Years
  • Type Course Post Graduate
  • stream Computer Science and IT
  • Delivery Mode
Written By universitykart team | Last updated date Jul, 07, 2024

The Post Graduate Programme in AI & Machine Learning syllabus at Great LearningGurgaon, Gurugram is designed to provide overall knowledge to the students with a strong foundation. Post Graduate Programme in AI & Machine Learning faculty at Great LearningGurgaon specially focus on in-depth learning to relevant subjects. At first semester syllabus of Post Graduate Programme in AI & Machine Learning at Great LearningGurgaon, students learn the basics of programme. A strong foundation is very important for comprehensive learning. Post Graduate Programme in AI & Machine Learning syllabus at Great LearningGurgaon, Gurugram maintains a balance between theoretical knowledge and practical knowledge.

Post Graduate Programme in AI & Machine Learning first year students at Great LearningGurgaon are introduced with core subjects. Then they are encouraged to explore other area for a broader perspective. Great LearningGurgaon, Gurugram also provides practical training sessions, workshops, projects, and case studies to enhance student skills. Post Graduate Programme in AI & Machine Learning syllabus at Great LearningGurgaon, Gurugram is also frequently updated to give industry relevant training and knowledge to students. Great LearningGurgaon strives to provide a nurturing environment where students can learn new skills. The hands-on training sessions at Great LearningGurgaon enable Post Graduate Programme in AI & Machine Learning students to apply knowledge and skills in a controlled environment and get required experience.

According to syllabus of Post Graduate Programme in AI & Machine Learning progress, students learn advanced topics and complex concepts. The Post Graduate Programme in AI & Machine Learning curriculum at Great LearningGurgaon, Gurugram mainly focuses on analytical and critical thinking. As the Post Graduate Programme in AI & Machine Learning course unfolds, students develop several important skills that increases their employability. As per syllabus of Post Graduate Programme in AI & Machine Learning at Great LearningGurgaon also includes real-life projects and internship programs. It helps students critical thinking and gives them real-world experience.

Post Graduate Programme in AI & Machine Learning curriculum at Great LearningGurgaon includes group discussions, guest lectures, case studies, and skill development workshops to enhance the learning experience. The Post Graduate Programme in AI & Machine Learning syllabus at Great LearningGurgaon aims to create well-rounded professionals equipped with the necessary skills and knowledge to succeed in their chosen fields.

Additional curriculum at Great LearningGurgaon

  1. Workshops and Seminars - Regular sessions with industry experts help Post Graduate Programme in AI & Machine Learning students at Great LearningGurgaon to stay updated with current trends.
  2. Group Projects - Collaborative projects according to Great LearningGurgaon syllabus develop teamwork and problem-solving skills.
  3. Case Studies - Post Graduate Programme in AI & Machine Learning syllabus offers analysis of real-world scenarios to apply theoretical knowledge.
  4. Extracurricular Activities - Great LearningGurgaon 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 Great LearningGurgaon, Gurugram for latest Post Graduate Programme in AI & Machine Learning curriculum.

Syllabus & Subject: PGP in AI & Machine Learning Course  

The syllabus for a Post Graduate Program (PGP) in AI and Machine Learning is designed to provide students with a comprehensive understanding of artificial intelligence and machine learning technologies. It typically includes topics such as:

S.NoSubjects
1Introduction to Regression
2Mathematics Foundations
3Model Building using Least squares
4Overview of Feature Engineering
5Dimensionality Reduction
6Introduction to Unsupervised Learning, Clustering                                                            
7Topic modelling using LDA
8Introduction to Sentiment Analysis
9Artificial Neural Network
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