Program curriculum

  • 1

    Welcome to MLC!

    • Program overview

    • About Zaka

    • Meet your Zaka support team!

    • Download your MLC Boarding Kit

    • Program syllabus

    • Best practices & tips for success

    • Are you ready?

  • 2

    Week 0 - Orientation Week

    • 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

  • 3

    Week 1 - Data Science Foundations

    • 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

  • 4

    Week 2 - Machine Learning Foundations

    • 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

  • 5

    Week 3 - Machine Learning Foundations (continued)

    • 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

  • 6

    Week 4 - Statistical Model Validation & Testing

    • 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

  • 7

    Week 5 - Neural Networks & Deep Learning

    • 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

  • 8

    Week 6 - Deep Learning & Advanced Data Types

    • 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

  • 9

    Week 7 - Deep Learning & Advanced Data Types (continued)

    • 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

  • 10

    Week 8 - Machine Learning in Production

    • 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

  • 11

    Week 9 - Machine Learning in Research

    • 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

  • 12

    Week 10 / 11 - Capstone Projects & Career Fair Prep

    • 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!

  • 13

    Week 12 - Career Fair

    • Career Fair Schedule & Final Presentation Expectations

    • GatherTown Platform Demo

    • MLC Closing Ceremony - Thursday, September 23