Published 8/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Master Python Programming and Dive into the World of AI: A Beginner-Friendly Journey from Coding Basics to AI Concepts
What you’ll learn
Gain a strong understanding of Python, including data types, operators, control structures, functions, and classes, enabling you to write efficient and organize
Apply Python concepts to solve real-world problems, automate tasks, and create projects, enhancing your logical and algorithmic thinking.
Use Python libraries like TensorFlow, Keras, and scikit-learn to build, train, and evaluate basic AI models, gaining hands-on experience in AI and ML.
Requirements
Basic Computer Skills: Familiarity with using a computer, including navigating files and installing software, will be helpful but not mandatory.
A Willingness to Learn: Bring your enthusiasm and curiosity! A proactive attitude towards learning will help you get the most out of the course.
Access to a Computer and Internet Connection: You’ll need a computer (Windows, macOS, or Linux) with internet access to download and install Python, follow along with the lessons, and practice coding.
Description
Overview
Section 1: Introduction to Python Programming
Lecture 1 Module 1: Introduction to Python Programming
Section 2: Module 2: Control Flow in Python
Lecture 2 Control Flow in Python
Section 3: Module 3: Functions and Modules in Python
Lecture 3 Module 3: Functions and Modules in Python
Section 4: Module 4: Working with Files and Data
Lecture 4 Working with Files and Data
Section 5: Module 5: Introduction to Object-Oriented Programming (OOP) in Python
Lecture 5 Introduction to Object-Oriented Programming (OOP) in Python
Section 7: Module 7: Data Preprocessing and Visualization
Lecture 7 Data Preprocessing and Visualization
Section 8: Module 8: Supervised Learning Techniques
Lecture 8 Supervised Learning Techniques
Section 9: Module 9: Unsupervised Learning Techniques
Lecture 9 Unsupervised Learning Techniques
Section 10: Module 10: Introduction to Neural Networks and Deep Learning
Lecture 10 Introduction to Neural Networks and Deep Learning
Section 11: Module 11: Final Capstone Project
Lecture 11 Final Capstone Project
