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4G curriculum (older)

For students clearing pending subjects of the 4G scheme (7-digit subject codes, e.g. 4341602). Students admitted under the current scheme study the 5G curriculum.

4351601 · Semester 5 · 4G scheme

Foundation of AI and ML

Notes and solutions following the Gujarat Technological University (GTU) syllabus for 4351601. Independent material — not issued by the university.

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Materials

Syllabus

The official syllabus this material follows.

  • Syllabus

    8 pages

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Complete Book

The whole syllabus, unit by unit, written for the exam.

Problem Solver

Step-by-step solutions to typical problems.

PYQ Solutions

Past university papers, fully solved.

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    131 pages · English + ગુજરાતી

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  • Solved past papers — short answers

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Syllabus units

Unit 1: Fundamentals of Artificial Intelligence (AI)6 h · 10 marks
  • Artificial Intelligence Introduction
  • Artificial Intelligence Areas
  • AI applications in various industries
Unit 2: Foundation of Machine Learning (ML)9 h · 12 marks
  • What is Machine Learning? Well-Posed learning Problem
  • Types of Machine Learning
  • Reinforcement Learning
  • Comparison between Supervised, unsupervised and reinforcement learning
Unit 3: Foundation of Neural Networks9 h · 16 marks
  • Introduction to Neural Networks
  • Types of Activation Functions
  • Architectures of Neural Network
  • Learning Process in ANN
  • Back Propagation
Unit 4: Foundation of Natural Language Processing (NLP)9 h · 16 marks
  • Introduction To NLP
  • Components of NLP
  • Phases of NLP
  • Data Preprocessing Using NLTK
  • Types of Ambiguities in NLP
Unit 5: Word Embedding in Natural Language Processing9 h · 16 marks
  • Word Embedding techniques
  • Challenges with TF-IDF and BoW, Pre Trained word Embedding
  • Applications of NLP

About this course

Artificial Intelligence (AI) and Machine Learning (ML) technologies have immense growth potential and are expected to shape the future of various fields. Understanding AI and ML gives learners a competitive edge in today's era. This course provides the foundation concepts of AI and ML. It covers topics such as Fundamentals of AI, Types of machine learning, Artificial Neural Networks (ANN) and Natural Language Processing (NLP). ANN and NLP is an integral part of the broader field of Artificial Intelligence (AI). This helps students to develop basic models of neural network to solve real world problems.