Artificial Intelligence & Machine Learning
Learn Machine learning from the best in the industry.
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Welcome Message
Course Intro
What is Machine Learning
Applications of Machine Learning
Join Developer Community
AI vs Ml vs DL
Types of Learning
Machine Learning LifeCycle
Traditional Software Engineering vs Machine Learning
Basics Summary
Machine Learning Basics Quiz
Student Feedback - Fundamentals
Python - Course Preview
Python - What is Python
Python - Who should Learn Python?
Python - Why Python?
Python - How to learn Python
Python - Basics Of Programming
Python - Installation & Setup
Python - My First Python Program
Python - Instruction Execution
Python - Variables
Python - Taking User Input
Python - Build Calculator Exercise
Python - Strings from Beginning
Python - String Manipulation
Python - Working With Numbers
Python - Intro to DataStructures
Python - Lists in Python
Python - List Methods
Python - Number List Manipulation
Python - Tuples
Python - If Else Statements
Python - Logical Operators
Python - Comparison Operators
Python - Build a Converter App
Python - Loops Intro
Python - While Loop
Python - Guessing Game Project
Python - For Loops In Python
Python - 2D Lists & Nested Loops
Python - Dictionaries
Python - Functions Intro
Python - Parameters in Functions
Python - Return Statements in Functions
Python - Word Counter Exercise
Python - Intermediate Project - Student Management System
Python - Handling Errors
Python - Generic Exceptions & Finally
Python - Modules
Python - Packages in Python
Python - File IO
Python - Object Oriented Programming (OOPs)
Python - Classes and Objects
Python - PyPI And Pip
Python - Coding Standards
Python - Price Tracker App - Intro
Python - Web Scraping Using Beautiful Soup
Python - Parsing Data
Python - Dynamic Multiple Inputs
Python - Price Check Logic
Python - Write Output File
Python - Project Wrap Up
Student Feedback - Python
Certification Instructions
Jupyter Notebook Setup
Google Colab - Intro & Basic Setup
DataSet - What, Where , How
Kaggle Intro
Kaggle - Building a Profile
Kaggle - Working with Notebooks
Kaggle - Sharing a Notebook
Kaggle - Dataset Upload
Kaggle - Link Dataset to Notebook
Assignment: Getting comfortable with Kaggle
Foundations - Kaggle quiz
Python Fundamentals Recap
Python Recap Installing Library
Data Visualization using Python - Intro to Matplotlib
Intro to Numpy in Python
Intro to Pandas in Python
Intro to PIL/OpenCV
ML Frameworks - Intro to Scikit-learn, TensorFlow, Pytorch
Assignment: Getting comfortable with pandas, numpy, matplotlib
Python recap quiz
Join Developer Community
Student Feedback - ML Basics
Referral Program
Intro to Linear Regression
Linear Regression - Understanding Data
Linear Regression - Loading Data
Linear Regression - Build & Test a Model
Linear Regression Quiz
Linear Regression - Finding Linearity
Linear Regression - Understanding Linear Function and Slope
Linear Regression - Merging Math Line & Training Data
Linear Regression - Manual Training Line of Best Fit Regression Line
Linear Regression - Root Mean Squared Error
Linear Regression - Inferencing
Linear Regression - Coefficient & Intercept
Linear Regression - Bias & Variance
Linear Regression - UnderFitting vs Overfitting
Linear Regression Summary
Student Feedback - Linear Regression
Logistic Regression Intro
Logistic Regression - Data Setup
Logistic Regression - Data Cleanup & Feature Engineering - Part 1
Logistic Regression - Data Cleanup & Feature Engineering - Part 2
Logistic Regression - Data Cleanup & Feature Engineering - Part 3
Logistic Regression - Predicting Future Tips Data - Part 1
Logistic Regression - Predicting Future Tips Data - Part 2
Logistic Regression - Predicting Future Tips Data - Part 3
Logistic Regression - Predicting Future Tips Data - Part 4
Logistic Regression - Predicting Future Tips Data - Part 5
Logistic Regression - Theoretical Understanding - Part 1
Logistic Regression - Theoretical Understanding - Part 2
Logistic Regression - Theoretical Understanding - Part 3
Logistic Regression Summary
Intro to Linear Regression
How ML Algorithms Learn - Part 1
How ML Algorithms Learn - Part 2
How ML Algorithms Learn - Part 3
Student Feedback - Logistic Regression
Naive Bayes - Intro
Naive Bayes - Classification vs Regression
Naive Bayes - What is Customer Segmentation
Naive Bayes - Data Cleanup And Feature Engineering
Naive Bayes - Train & Test
Naive Bayes - Confusion Matrix
Naive Bayes - How it Works?
Naive Bayes - Summary
Student Feedback - Naive Bayes
Decision Tree - Overview
Decision Tree - Understanding DataSet
Using Decision Tree
What is Decision Tree
How To Use Decision Tree
How to Use Decision Tree Continued
Decision Tree - Genie Impurity
Visualize Decision Tree Model
Random Forest
Decision Tree - Summary
Student Feedback - Decision Tree
Intro to Image Processing
Intro to Capstone Project
Pipeline Of Image Processing
Convert Image Data to Features - Part 1
Convert Image Data to Features - Part 2
Train & Evaluate Model
Model Saving & End-To-End Prediction
What did you feel about the entire Course
Capstone Summary
What to Learn Next
Project Intro
Project Option 1
Project Option 2
Referral Program
ML Architect
Machine Learning Engineer at Datoin