Introduction
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Sno |
Topic |
Learn
& Review |
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1 |
Introduction to Artificial
Intelligence (AI) |
Introduction to Al: Foundational
Concepts What is Intelligence? Decision Making. How do you make decisions? Make Your Choices! What is Artificial Intelligence?
How do machines become
Artificially Intelligent? Applications of Artificial
Intelligence around us What is not Al? Introduction to Al: Basics of Al
AI, ML & DL Introduction to Al Domains Data Sciences Computer Vision Natural Language Processing. Al Ethics Moral Issues: Self-Driving Cars Data Privacy Al Bias Al Access |
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2 |
AI Project Cycle |
Introduction Problem Scoping 4Ws Problem canvas Data Acquisition Data Features Data Exploration Modelling Rule Based approach Learning Based Approach Supervised Learning Classification Regression Unsupervised Learning Clustering Evaluation Neural network |
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3 |
Advance Python |
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4 |
Data Science |
Introduction, Applications of Data Sciences, Revisiting AI Project Cycle, Data Collection, Data Access |
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5 |
Computer Vision |
Introduction Applications of Computer Vision Computer Vision: Getting
Started. Computer Vision Tasks. Classification Classification + Localisation Object Detection. Instance Segmentation Basics of Images Basics of Pixels Image Features Introduction to OpenCV. |
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6 |
Natural Language Processing |
Natural Language Processing. Introduction Applications of Natural Language
Processing Getting Started Revisiting the Al Project Cycle Chatbots Human Language VS Computer
Language Arrangement of the words and
meaning Multiple Meanings of a word Perfect Syntax, no Meaning Data Processing Text Normalisation Bag of Words TFIDF |
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7 |
Evaluation |
Introduction What is evaluation? Model Evaluation Terminologies The Scenario Confusion matrix Evaluation Methods Accuracy Precision Recall Which Metric is Important? F1 Score |
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8 |
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9 |
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10 |
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