DELETE Machine Learning Certification
In 12 intensive weeks, you will gain the skills necessary to speak the Machine Learning language, build the toolkit you need to enter the Machine Learning market, and take your career to the next level.
Program overview
About Zaka
Meet your Zaka support team!
Download your MLC Boarding Kit
Program syllabus
Best practices & tips for success
Are you ready?
Week kick-off
MLC Launch Webinar - Recording Available
Prepwork - Get Ready!
Guidelines to Google Colaboratory's environment
Download - Prepwork cheat sheet
Download - Capstone Project Requirements
Welcome to Week 1!
Outline of the week
Week Schedule & Important Notes
Project Expectations Webinar - Recording available
Download - Week 1 Slides
Data Science Lifecycle
Test your Zaka - DS Lifecycle
EDA Overview
Basic steps of EDA
Test your Zaka - EDA
Data Munging & Wrangling
Test your Zaka - Data Munging
Data Visualization
Case Study: Covid-19 outbreak visualization
Test your Zaka - Data Visualization
Visualizations with Matplotlib
Important Reminder!
Tip! - Refer to Python's documentation
Hands-on: Visualizations with Matplotlib - part 1
Hands-on: Visualizations with Matplotlib - part 2
Hands-on: Visualizations with Matplotlib - part 3
Additional Practice: Visualizations with Seaborn
Data Cleaning
Data Cleaning - Step 1: Diagnosis
Data Cleaning - Step 2: Cleaning
Data Cleaning - Step 3: Finding Correlations
Test your Zaka - Data cleaning
Hands-on: Data Cleaning - Introduction
Hands-on: Data Cleaning - part 1
Hands-on: Data Cleaning - part 2
Hands-on: Data Cleaning - part 3
Hands-on: Data Cleaning - part 4
Tip! - Begin your weekly challenge
Data Manipulation
Test your Zaka - Data Manipulation
Hands-on: Data Manipulation - Introduction
Hands-on: Data Manipulation - part 1
Hands-on: Data Manipulation - part 2
Hands-on: Data Manipulation - part 3
Hands-on: Data Transformation - Introduction
Hands-on: Data Transformation
Feature Engineering
Issues with Features
Test your Zaka - Feature Engineering
Documentation & Reporting
Your Full Data Science Project
Hands-on: Full Data Science Project - Introduction
Hands-on: Full Data Science Project - EDA - part 1
Hands-on: Full Data Science Project - EDA - part 2
Hands-on: Full Data Science Project - EDA - part 3
Hands-on: Full Data Science Project - EDA - part 4
Hands-on: Full Data Science Project - Data Cleaning - part 1
Hands-on: Full Data Science Project - Data Cleaning - part 2
Hands-on: Full Data Science Project - Data Cleaning - part 3
Hands-on: Full Data Science Project - Modeling - part 1
Hands-on: Full Data Science Project - Modeling - part 2
Hands-on: Full Data Science Project - Modeling - part 3
Data Acquisition
Data Types
Test your Zaka - Data Types
Databases
Data Warehouses
Test your Zaka - Databases & Data Warehouses
Challenge of the Week!
Download - Challenge Requirements
Download - Week's Run-through
Download - Week's Deep Dive
Welcome to Week 2!
Outline of the week
Week Schedule & Important Notes
Tuesday-July 13-Office Hours - Recording available
Download - Week 2 Slides
Intro to Machine Learning
Classes of Machine Learning
Types of ML Algorithms
Test your Zaka - Intro to ML
Supervised Learning
Types of Supervised Learning
Supervised Learning Applications
Test your Zaka - Supervised Learning
k-Nearest Neighbors
Test your Zaka - kNN
Linear Regression
Error Functions & Evaluation Metrics for Regression
How to find the best fitting line?
Test your Zaka - Linear Regression
Gradient Descent
Cost Function Derivative
Test your Zaka - Gradient Descent
Hands-on: Linear Regression from Scratch - Introduction
Hands-on: Linear Regression from Scratch - part 1
Hands-on: Linear Regression from Scratch - part 2
Tip! - Begin your weekly challenge
Multi-linear Regression
Logistic Regression
Error Functions for Classification
Test your Zaka - Logistic Regression
Evaluation Metrics for Classifiers
Test your Zaka - Evaluation Metrics for Classifiers
Hands-on: Logistic Regression from Scratch - Introduction
Hands-on: Logistic Regression from Scratch - part 1
Hands-on: Logistic Regression from Scratch - part 2
What do ML models have in common?
Challenge of the Week!
Download - Challenge Requirements
Download - Week's Run-through
Download - Week's Deep Dive
Welcome to Week 3!
Outline of the week
Week Schedule & Important Notes
Download - Week 3 Slides
Naive Bayes
Naive Bayes - Example
Tip! - Solve Examples by Hand
Test Your Zaka: Naive Bayes
Decision Trees
How to Build Decision Trees? - Intuition
Method 1: Information Gain
Method 2: Gini Index
Decision Forests
Test Your Zaka: Decision Trees
Hands-on: Naive Bayes & Decision Trees - Introduction
Hands-on: Naive Bayes & Decision Trees - Data Loading
Hands-on: Naive Bayes Implementation
Hands-on: Decision Trees Implementation
Support Vector Machines (SVMs)
SVM Loss
Non-linear SVM & Kernel Transformations
Test Your Zaka: SVM
Hands-on: SVM - Introduction
Hands-on: SVM - Data Loading
Hands-on: Linear SVM
Hands-on: Non-linear SVM
Intro to Unsupervised Learning
Clustering Methods
K-means Clustering
Test Your Zaka: Clustering Methods
Association Analysis
Association Analysis - Example
Test Your Zaka: Association Analysis
Hands-on Workshop on Unsupervised Learning - part 1 - Recording available
Hands-on Workshop on Unsupervised Learning - part 2 - Recording available
Challenge of the Week!
Download - Challenge Requirements (Part A)
Important Reminder - Solve Part A first!
Download - Challenge Requirements (Part B)
Download - Week's Run-through
Download - Week's Deep Dive
Welcome to Week 4!
Outline of the week
Week Schedule & Important Notes
Human-centered Design Thinking Workshop - part 1 - Recording available
Human-centered Design Thinking Workshop - part 1 - Slides available
Download - Week 4 Slides
Evaluating ML Models
Holdout Method
K-Fold Method
Evaluation Metrics - Review
Test your Zaka - Evaluating ML Models
Hands-on: Evaluating ML Models - introduction
Hands-on: Evaluating ML Models
Comparing ML Models
Z-Score Test
McNemar Test
Test your Zaka - Comparing ML Models
Hands-on: Comparing ML Models - introduction
Hands-on: Comparing ML Models
Tip! - Begin your weekly challenge
1. Defining the Problem - ML Workflow
2. Data Preparation - ML Workflow
Data-related Challenges
3. Modeling & related Challenges - ML Workflow
Bias & Variance
Overfitting & Underfitting
Test your Zaka - ML Workflow & Common Challenges
Data Methods for Improving ML Models
Model Design Methods for Improving ML Models - Vary Complexity
Model Design Methods for Improving ML Models - Hyperparameter Tuning
Model Design Methods for Improving ML Models - Ensemble Methods
Test your Zaka - Improving ML Models - part 1
Optimization Methods for Improving ML Models - Regularization
Types of Regularizers
Test your Zaka - Improving ML Models - part 2
Hands-on: Improving ML Models - introduction
Hands-on: Improving ML Models
Challenge of the Week!
Download - Challenge Requirements (Part A)
Download - Challenge Requirements (Part B)
Download - Week's Run-through
Download - Week's Deep Dive
Welcome to Week 5!
Outline of the week
Week Schedule & Important Notes
To Do: Complete this Exercise before Wednesday's HCD Workshop
Human-centered Design Thinking Workshop - part 2 - Recording Available
Solving Backpropagation from SCRATCH Hands-on Workshop - Recording Available
Download - Week 5 Slides
Intro to Neural Networks & Deep Learning
What are Neural Networks?
Activation Functions
Feedforward Neural Networks
Neural Network Hyperparameters
How do Neural Networks Learn?
Important Note: Do Not Fear the Math!
Step 1 - Feed Forward
Step 2 - Cost Function
Step 3 - Backward Pass - Derivatives of the Final Output Layer
Step 3 - Backward Pass - Derivatives of Hidden Layers
Step 4 - Weights and Bias Updates
Practice & Solve Backpropagation Yourself!
Training a Neural Network
Intro to Tensorflow Keras
Hands On: Build DL Models
Evaluating Performance of DL Models
Cross Validation
Hands On: Pima binary classification
Hands On: Cross Validation
Data Preparation
Hands On: Classification
Hands On: Regression
Improving DL Models - Data Methods
Improving DL Models - Model Design Methods - part 1
Improving DL Models - Model Design Methods - part 2
Improving DL Models - Optimization Methods - GD Variants
Improving DL Models - Optimization Methods - GD Optimization Algorithms
Improving DL Models - Optimization Methods - Regularization
Improving DL Models - Optimization Methods - Early Stopping
Hands On: Advanced Concepts
Challenge of the Week!
Download - Challenge Requirements
Download - Week's Run-through
Download - Week's Deep Dive
Welcome to Week 6!
Outline of the week
Week Schedule & Important Notes
Download - Week 6 slides
Why Do Deep Learning Architectures Differ across Data Types?
Part 1 of the Week - Computer Vision
What is Computer Vision?
Challenges of Computer Vision
Image operations
Hands-on: Image Operations
Convolution operation
Hands-on: Image processing
Image Data Preparation
Hands-on: Image Data Preparation - part 1
Hands-on: Image Data Preparation - part 2
Image Augmentation
Hands-on: Image Data Augmentation
Deep Learning for Computer Vision
Convolutional Neural Networks (CNN)
Pooling layers
Hands-on: Convolutions & Pooling - Part 1
Hands-on: Convolutions & Pooling - Part 2
How to deal with limited data?
Transfer Learning & Advanced Architectures
Hands-on: Advanced CNN architectures
CNNs for Different CV Tasks
YOLO (You Only Look Once)
Part 2 of the Week - Natural Language Processing
Natural Language
Challenges of Natural Language
NLP applications
Text cleaning
Hand-on: Text data pre-processing
Feature extraction using Bag-of-words
Hands-on: Bag-of-words
Hands-on: Sentiment Analysis - part 1
Hands-on: Sentiment Analysis - part 2
Word Embeddings
Hands-on: Word Embeddings - Part 1
Hands-on: Word Embeddings - Part 2
Download - Week's Run-through
Download - Week's Deep Dive
Welcome to Week 7!
Outline of the week
Week Schedule & Important Notes
An Intro to Reinforcement Learning Workshop - slides available
An Intro to Reinforcement Learning Workshop - recording available - part 1
An Intro to Reinforcement Learning Workshop - recording available - part 2
Download - Week 7 slides
Part 1 of the Week - Natural Language Processing
Keras' Embedding layer
Sequence problems
Intro to Recurrent Neural Networks
Hands-on: Deep Sentiment Analysis - Part 1
Hands-on: Deep Sentiment Analysis - Part 2
Test your Zaka
Breaking Down Recurrent Neural Networks
Variants of RNN Architectures
Part 2 of the Week - Time-series Analysis & Prediction
What are Time-series?
Features of Time-series sequences
Test your Zaka
Types of Time-series problems
Supervised Learning with Time-series Data
Test your Zaka
Understanding Time-series datasets
Hands-on: Case study on power prediction
Hands-on: Dataset loading
Hands-on: Data inspection
Hands-on: Data cleaning - part 1
Hands-on: Data cleaning - part 2
Hands-on: Data preprocessing
Test your Zaka
Preparing Time-series datasets
Hands-on: Data preparation - part 1
Hands-on: Data preparation - part 2
Hands-on: Data preparation - part 3
Test your Zaka
Building Time-series models
Hands-on: Model training
Test your Zaka
Evaluating Time-series models
Hands-on: Model evaluation - part 1
Hands-on: Model evaluation - part 2
Hands-on: Visualizing model performance
Test your Zaka
Hands-on: Data visualization
Download - Week's Run-through
Download - Week's Deep Dive
Welcome to Week 8!
Introduction
Outline of the week
Week Schedule & Important Notes
LIVE: Big Data: Chronicles from the Field - Recording available
LIVE: Hands-on Workshop on ML in Production - Recording available
Download - Week 8 Slides
Phase 1: Planning and Project Setup
Test Your Zaka - Planning and Project Setup
Phase 2: Data Collection and Labeling
Data Collection
Data Storage
Data Labeling
Demo: LabelStudio
Data Versioning
Data Privacy
Recap
Test your Zaka - Data Collection and Labeling
Phase 3: Model Training and Debugging
Writing Code
How to use Git?
Hands-on: How to use Git
Computing Hardware
Cloud
Linux Commands
Model Training
Hands-on: Experiment Tracking using MLFlow - part 1
Hands-on: Experiment Tracking using MLFlow - part 2
Demo: AWS SageMaker - part 1
Demo: AWS SageMaker - part 2
Model Testing
Testing ML Systems
Recap
Test your Zaka - Model Training and Debugging
Phase 4: Model Deploying and Monitoring
Deploying / Serving Models
Cloud Deployment
Hands-on: Deploying ML Models with Flask and Docker
Performance Optimization
Hands-on: Compressing ML Models
Edge Deployment
Monitoring Model Performance
MLOps
Recap
Test your Zaka - Model Deploying & Testing
Download - Week's Run-through
Download - Week's Deep Dive
Welcome to Week 9!
Week Schedule & Important Notes
Monday LIVE - recording available
Tuesday LIVE - recording available
Wednesday LIVE - recording available
Thursday LIVE - recording available
Saturday LIVE - recording available
Week's Schedule & Important Notes
LIVE: Kick-off Session - recording available
Action Required: Book your Mentoring Slots
Action Required: Book your Mock Interview
Tips on Mastering Your Interview
Tips on Designing a Killer CV
Wednesday Talk - Channeling your Career into Data Science - recording available
Thursday Talk - How to Ace your Online Presentations - recording available
Friday Talk - Job Search 101: How to Land Interviews without Applying Online - recording available
Saturday Talk - Agile... the why!
Career Fair Schedule & Final Presentation Expectations
GatherTown Platform Demo