AI and Machine Learning

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About Course

Course Description:

This 30-hour certificate course in Artificial Intelligence and Machine Learning will provide students from diverse academic backgrounds with a foundational understanding of these cutting-edge technologies. AI and Machine Learning are transforming various industries, and this course aims to equip students with the knowledge and skills necessary to leverage the power of data-driven decision-making, automation, and intelligent systems.

Target Audience:

Undergraduate students from all streams with an interest in AI and Machine Learning.

Course Objectives:

  • Understand the fundamental concepts and applications of AI and Machine Learning.
  • Learn how to apply AI and Machine Learning techniques to real-world problems.
  • Gain hands-on experience with AI tools and frameworks.
  • Explore ethical and societal implications of AI and Machine Learning.
  • Develop a basic project demonstrating AI and Machine Learning capabilities.

Course Duration: 30 hours


Module 1: Introduction to AI and ML (2 hours)

  • What is Artificial Intelligence?
  • What is Machine Learning?
  • Types and applications of AI and ML.
  • Ethical considerations in AI and ML.

Module 2: Data Preprocessing (2 hours)

  • Data collection and cleaning.
  • Feature selection and engineering.
  • Data scaling and normalization.

Module 3: Supervised Learning (4 hours)

  • Linear Regression.
  • Logistic Regression.
  • Decision Trees and Random Forests.
  • Support Vector Machines.
  • Model evaluation and selection.

Module 4: Unsupervised Learning (4 hours)

  • Clustering techniques (K-Means, Hierarchical).
  • Principal Component Analysis (PCA).
  • Anomaly detection.

Module 5: Natural Language Processing (6 hours)

  • Introduction to Neural Networks.
  • Tokenization and Text Preprocessing.
  • Text Classification with NLP.
  • Speech Processing.

Module 6: Hands-on Projects (8 hours)

  • Students work on small AI and ML projects to apply the knowledge gained.

Module 7: Ethics and Future Trends (2 hours)

  • Ethical considerations in AI.
  • Future trends in AI and Machine Learning.

Module 8: Course Review and Certification (2 hours)

  • Review of key concepts and student projects.
  • MCQs and evaluation.


  • Continuous assessment through quizzes, assignments, and project work.
  • Final project presentation and report and MCQ Test.


No specific prerequisites are required, but a basic understanding of mathematics and programming (e.g., Python) is beneficial.


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