Course Content
Introduction to AI and Data Science
Duration: 1-2 Weeks
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Understanding the fundamentals of AI and Data Science
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Exploring industry applications and job roles
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Learning about the ethical considerations in AI and Data Science
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Introduction to relevant tools and software, such as Python, R, SQL, and Tableau etc.
00:00
Data Analysis and Visualization
Duration: 3-4 Weeks
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Data preprocessing and cleaning using Pandas and NumPy libraries
00:00
Visualization techniques and tools like Matplotlib and Seaborn
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Hands-on practice with industry-standard data analysis tools.
00:00
Fundamentals of Machine Learning
Duration:
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Understanding supervised and unsupervised learning techniques
00:00
Implementation of machine learning algorithms using Scikit-learn
00:00
Introduction to model evaluation and hyperparameter tuning
00:00
Deep Learning Essentials
Duration: 7-8 Weeks
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Introduction to deep learning concepts and neural networks
00:00
Hands-on experience with TensorFlow and Keras for building and training neural networks
00:00
Application of deep learning in image and text data
00:00
Natural Language Processing (NLP) and Text Mining
Duration: 9-11 Weeks
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Fundamentals of NLP using NLTK and SpaCy libraries
00:00
Text preprocessing, feature extraction, and sentiment analysis
00:00
Hands-on application of NLP techniques in real-world datasets
00:00
Capstone Project and Assessment
Duration: 12-13 Weeks
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Application of AI and Data Science concepts in a real-world project
00:00
Evaluation through quizzes, tests, and project presentations
00:00
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Understanding the fundamentals of AI and Data Science

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