Python Ai: Build Smart Assistants & Computer Vision Projects

Create AI-powered assistants and develop real-time face detection and emotion recognition systems with Python.

What you'll learn

Master the fundamentals of Python programming for building AI assistants

Develop computer vision skills to implement real-time face detection and recognition

Integrate advanced AI features like speech recognition and wake-up word functionality

Create hands-on AI projects combining Python, computer vision, and AI assistant development What are the re

Requirements

Basic understanding of Python programming (preferred but not required)

No prior experience in AI or computer vision is necessary

A computer with Python and Visual Studio Code installed

Description

In this comprehensive course, you will learn how to build your very own AI-powered assistant while mastering computer vision techniques. Starting from scratch, you'll gain hands-on experience in Python programming, which is essential for developing intelligent applications. The course covers the basics of building an AI assistant, including text-to-speech, speech recognition, and wake-up word functionality, all the way to advanced computer vision concepts like real-time face detection, face recognition, and emotion analysis. Whether you’re a beginner looking to explore AI and computer vision or an intermediate developer wanting to level up your skills, this course provides the perfect balance of theory and practical applications. You’ll work on exciting projects that integrate AI with computer vision, making it easy to apply your knowledge in real-world scenarios. By the end of the course, you will have developed several complete AI projects and a solid understanding of Python, AI, and computer vision technologies, which are in high demand across industries. You will also learn how to troubleshoot and optimize your AI models for better performance and accuracy. This course will provide you with the skills needed to build professional-level AI applications, setting you up for success in the rapidly growing AI and software development fields.

Overview

Section 1: Introduction for AI Assistant

Lecture 1 Introduction Video

Lecture 2 Installing Python on Windows

Lecture 3 Installing Python on MacOS

Lecture 4 Installing Python on Linux

Lecture 5 Installing VS Code on Windows

Lecture 6 Installing VS Code on MacOS

Lecture 7 Installing VS Code on Linux

Section 2: Setting Up the Project Environment

Lecture 8 Creating the Project Folder Structure

Lecture 9 Installing Required Libraries

Section 3: Text-to-Speech Conversion

Lecture 10 Pyttsx3 Library in Python

Lecture 11 pyttsx3 Library Customization

Section 4: Speech Recognition

Lecture 12 Introduction to Speech Recognition

Section 5: Understanding Intent Recognition

Lecture 13 Implementing intent recognition in python

Section 6: Wake Up Word

Lecture 14 Wake Up Word for AI Assistant

Section 7: Building the Core Functionality

Lecture 15 AI Assistant Project Part-I

Lecture 16 AI Assistant Project Part-II

Lecture 17 AI Assistant Project Part-III

Section 8: Advanced Features

Lecture 18 Dictionary Feature

Lecture 19 Translation Feature

Lecture 20 Time Feature

Lecture 21 Date Feature

Lecture 22 Translation Feature Part-II

Lecture 23 UPDATE!!

Lecture 24 Wikipedia Search Feature

Lecture 25 Wikipedia Function Update

Lecture 26 Device Lock Feature

Lecture 27 Device Lock on MacOS and Linux

Section 9: Final Project Overview

Lecture 28 Final Project Overview

Section 10: Conclusion and Next Steps-Python AI Assistant

Lecture 29 Conclusion-Python AI Assistant

Lecture 30 Download Project

Section 11: Introduction to OpenCV

Lecture 31 Overview of OpenCV

Section 12: Setting Up Development Environment

Lecture 32 Setting Up Development Environment

Section 13: Basics of OpenCV

Lecture 33 Reading and Displaying an Image using OpenCV

Lecture 34 Cropping an Image using OpenCV

Lecture 35 Resizing an Image using OpenCV

Lecture 36 Saving Cropped and Resized Images using OpenCV

Section 14: Project 1: Basic Image Manipulation (Beginner Level)

Lecture 37 Drawing Shapes

Lecture 38 Adding Text

Lecture 39 Applying Transformations and Advanced Image Enhancements

Lecture 40 Section Recap - Project 1

Section 15: Project 2: Real-Time Face Detection (Intermediate Level)

Lecture 41 Real-Time Face Detection - Part 1

Lecture 42 Real-Time Face Detection - Part 2

Lecture 43 Section Recap - Project 2

Section 16: Face Recognition using FER (Advanced Level)

Lecture 44 Facial Emotion Recognition using FER - Part 1

Lecture 45 Section Recap - Project 3

Section 17: Conclusion - OpenCV

Lecture 46 Conclusion - OpenCV

Section 18: Thank You and Conclusion- AI Assistant and OpenCV

Lecture 47 Thank You and Conclusion

Lecture 48 Final Words and Gratitude

Beginners eager to dive into Python programming and build AI assistants,Aspiring developers wanting to explore computer vision and AI technologies,Anyone interested in combining practical AI skills with real-world applications