Brain vs Machine - Study Material
Overview
Course Overview:
The Brain vs Machine course introduces students to the fascinating world of Artificial Intelligence (AI) and Machine Learning (ML).
Through hands-on projects, students will learn about the fundamental concepts and algorithms that power AI systems, and they will gain practical experience with Python and popular data science libraries like Pandas and NumPy.
What You Will Learn:
Introduction to AI — Learn the foundational principles of Artificial Intelligence and its impact on modern technology.
The Machine Learning Process — Understand the steps involved in developing machine learning models, from data collection to model deployment.
Python for AI — Get started with Python programming, tailored specifically for AI applications.
Python for AI - Part 2 — Dive deeper into Python coding techniques for building AI models.
Pandas and Numpy — Learn to manipulate and analyze data using Pandas and Numpy, essential libraries for data science.
Data Visualization — Master techniques to represent data visually, helping to uncover insights and patterns.
Supervised and Unsupervised Learning — Understand the differences between supervised and unsupervised learning and when to use each.
Implementation of Linear Regression — Learn how to implement and apply Linear Regression models to real-world data.
Decision Tree Algorithm — Explore how decision trees work and their role in machine learning.
Implementation of Decision Tree Algorithm — Apply decision tree algorithms in hands-on projects.
Learning Outcomes:
By the end of this course, students will have a solid understanding of AI and machine learning algorithms, be proficient in Python programming, and be able to apply concepts like Linear Regression and Decision Trees to solve problems.
Prerequisites:
Basic programming knowledge (preferably in Python).
Interest in data science and AI.
Course Highlights:
Introduction to machine learning algorithms and their real-world applications.
Hands-on projects using Python, Pandas, and NumPy.
Practical experience in data visualization and model implementation.
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