Week kick-off

LIVE: MLC Launch Webinar

MLC Launch Webinar - Recording Available

LIVE: Q&A Session

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

LIVE: Project Expectations

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

LIVE: Hands-on Workshop on Unsupervised Learning

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

LIVE: Human-centered Design Thinking Workshop - part 1

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

LIVE: Human-centered Design Thinking Workshop - part 2

Human-centered Design Thinking Workshop - part 2 - Recording Available

LIVE: Solving Backpropagation from SCRATCH

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

LIVE | An Intro to Reinforcement Learning

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

LIVE: Big Data: Chronicles from the Field - Recording available

LIVE: Hands-on Workshop on ML in Production

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: NLP in the Age of Transformers & Sesame Street

Monday LIVE - recording available

Tuesday LIVE: Ethics in AI

Tuesday LIVE - recording available

Wednesday LIVE: Conversational AI: Overview, Arabic Progress, & Trending Research

Wednesday LIVE - recording available

Thursday LIVE: Lifelong Learning for Chatbots in Customer Support

Thursday LIVE - recording available

Saturday LIVE: Diving into the Realm of Transfer Learning

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 - Sept 15: Channeling your Career into Data Science

Wednesday Talk - Channeling your Career into Data Science - recording available

Thursday Talk - Sept 16: How to Ace your Online Presentations

Thursday Talk - How to Ace your Online Presentations - recording available

Friday Talk - Sept 17: Job Search 101 - How to Land Interviews without Applying Online

Friday Talk - Job Search 101: How to Land Interviews without Applying Online - recording available

Saturday Talk - Sept 18: Agile... the why!

Saturday Talk - Agile... the why!

Career Fair Schedule & Final Presentation Expectations

GatherTown Platform Demo

MLC Closing Ceremony - Thursday, September 23