Course description

AI is one of the most fascinating and universal areas of computer science, with enormous future potential. AI has a tendency to make machines function like humans. You will gain knowledge from this course about the characteristics of agents, AI search techniques, and various software design techniques using Prolog. You'll learn about the potential, advantages, and restrictions of various artificial intelligence and machine learning techniques. To understand complex concepts and relate them to particular scenarios, you can employ a selection of AI and machine learning algorithms to address real-world challenges. The capacity to assess available learning strategies and choose the most effective ones to complete a task will also be provided by this course. Prolog programming allows you to create a variety of software agents. By the end of this course, you will be able to understand fundamentals of Artificial intelligence, machine learning, learning models & algorithms, prolog programming, software agents and etc. 

What will i learn?

  • Agents and Environments
  • Search Strategies
  • Knowledge Representation
  • Mathematical foundations for AI and ML
  • Machine Learning and its types
  • Classification and Clustering
  • Sentiment analysis
  • Prolog Programming


  • Basic understanding of programming languages.
  • A laptop/desktop to complete the lab sessions/practicals

Frequently asked question

This course is designed for anyone with a basic understanding of programming and a keen interest in artificial intelligence (AI) and machine learning (ML). Whether you're a student, a working professional in a non-technical field, or a programmer looking to explore AI and ML, this course provides a foundational understanding for all.

Participants are expected to have a fundamental understanding of programming concepts and a basic knowledge of mathematics, including algebra and statistics. Familiarity with a programming language like Python is beneficial, but not mandatory, as the course covers relevant programming aspects.

The course is structured in a modular format, starting with an introduction to AI and ML concepts. Topics covered include but are not limited to supervised and unsupervised learning, neural networks, data preprocessing, model evaluation, and ethical considerations in AI. Each module consists of video lectures, hands-on exercises, and quizzes to reinforce your understanding.

The course is designed to be flexible, allowing participants to learn at their own pace. Once enrolled, you will have access to the course materials, including video lectures and assignments. However, it's recommended to follow a structured schedule to make the most of the learning experience. There are no strict deadlines, but periodic assessments and quizzes are provided to track your progress.

Absolutely. We understand that learners may encounter challenges or have questions along the way. The course includes a dedicated discussion forum where participants can interact with instructors and fellow learners. Additionally, there will be periodic live Q&A sessions to address any queries. Technical support is available to assist with any issues related to the online platform or course materials.

Dr. M. Maragatharajan

Dr. M. Maragatharajan, presently working as an assistant professor in the school of computing science and engineering at VIT Bhopal University, Madhya Pradesh. He has more than 13 years of teaching experience and more than 8 years of research experience. During his tenure, he has served in a variety of administrative capacities. His area of research includes Machine learning and Data Science. He has a can-do attitude, an open mind, is straightforward, committed to lifelong learning, and is result-oriented. He has been actively involved in educational research, and his research papers have been published both in international conferences and in peer-reviewed journals. He has more than 20 journal articles in various journals, and 16 papers have been presented at conferences. He has addressed innumerable guest lectures, conducted and organized several Faculty Development Programme (FDP) trainings. He has published a textbook, and he has granted one patent. He is an editorial board member for various journals and conferences. He has completed many certifications, including EMC2 and LabVIEW. He is very eager to develop personality traits by attending workshops, seminars, and faculty development programmes. He has completed one consultancy project worth Rs. 15,000.

Rachit Patel 23bai10969



Beginner Friendly easy to learn, nice user interface and so much learned from Vityarthi .

Ayushman Kumar Mantri 23bsa10131









Skill level


Expiry period




Related courses