MicroDegree

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