Course Overview
This comprehensive AI course is designed to guide learners from the basics of Artificial Intelligence to building real-world machine learning models. The course begins with an Introduction and Overview that explains the purpose of AI, its importance in modern technology, and the skills required to succeed in the field. In the Basic Foundation section, you will explore core concepts such as “What is AI?”, the different types of AI, and its real-world applications across industries like healthcare, entertainment, finance, and education. You will also understand the key differences between AI, Machine Learning, and Deep Learning, setting a strong conceptual base for the rest of the course.
Next, the course moves into the Programming Foundation where you will learn Python—the most essential language for AI. You will cover Python basics including variables, loops, conditions, functions, and data structures such as lists, tuples, and dictionaries. You will also learn major Python libraries: NumPy for numerical operations, Pandas for data analysis, Matplotlib and Seaborn for data visualization. These tools will prepare you to work with datasets, create graphs, and perform efficient data processing—skills every AI engineer needs.
The Mathematics for AI section focuses on the essential math concepts used behind the scenes of all AI systems. You will learn about matrices and vectors used in neural networks, probability for decision-making models, statistics for data analysis, and calculus for optimization in machine learning algorithms. These topics are taught in a simple and practical manner, making it easy for beginners to understand.
Finally, in the Machine Learning module, you will dive into the core concepts that power modern AI. This includes supervised learning, unsupervised learning, and how to evaluate model performance using techniques like accuracy, confusion matrix, and cross-validation. You will also learn how to use the Scikit-learn library to build ML models step-by-step. By the end of this course, you will have a strong understanding of AI, the ability to analyze data, build ML models, apply visualizations, and confidently work on real-life AI projects.
FAQ
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Basic computer knowledge like using a computer, browsing the internet, and handling files.
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Basic programming knowledge, especially Python, to understand how AI systems are built.
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Interest in learning how machines think, learn, and make decisions.
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Basic logical thinking to understand different types and their abilities.
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Interest in technology and smart tools.
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Understand what is Artificial Intelligence (AI).
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Identify real-world applications of AI in daily life.
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Understand examples such as self-driving cars and voice assistants.
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Understand the four types of AI based on functionality.
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Understand the difference between AI, ML, and DL
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Understand and use the ndarray for storing numerical data.
Requirment
Outcomes
Internships
No internships
Course curriculum
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29.00 ₹
- 2 Students
- 01h 05m
- Tamil (தமிழ்)
- beginner Level
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