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This is a 4 month practical bootcamp that puts you on the fast-track to becoming a Machine Learning Engineer:

  • It starts from the basics of Machine and Deep Learning using a CRISP-DM Methodology
  • It looks at internal mechanism of some of the most popular ML algorithms such as Linear Regression, Logistic Regression, Decision Trees, Ensemble Learning such as Random Forest and XGBoost, as well Neural Networks for Deep Learning.
  • It then goes on to the packaging and deployment of ML/DL models with Docker, Flask and BentoML to cloud services
  • The cloud services used are AWS EC2 and Lambda (for serverless computing)
  • Additionally, it covers some essential advanced topics such as working with tflite and TensorFlow serving, as well as Kubernetes and KServe
  • Finally, it ties everything together with 2-3 student-led projects that employ the tools and knowledge learned in the bootcamp

The highlights of the course are:

  • Focus on collaborative problem solving, getting hands on with git and sharing in public via notes and write-ups
  • It also includes weekly homeworks that serve as a guided walk-through of the concepts learned during the week
  • Peer-reviewing and evaluation of projects
Dates Coursework Link Dataset Used Notes Homework Link Dataset Used Solution Link
5-12 September 2022 Week 1: Intro to ML/Environment Setup --- Linear Algebra refresher Homework 1 Car Dataset Solution Jupyter notebook
13-19 September 2022 Week 2: Linear Regression Car Dataset Visual overview for structuring a ML project Homework 2 California Housing Prices Solution Jupyter notebook
20-26 September 2022 Week 3: Classification Telco Customer Churn Visual overview of EDA + Feature Engineering Homework 3 California Housing Prices Solution Jupyter notebook
27-03 Sep-Oct 2022 Week 4: Evaluation of ML Models Telco Customer Churn Detailed ROC curve & evalaution metrics overview Homework 4 AER Credit Card Data Solution Jupyter notebook
04-10 October 2022 Week 5: ML Deployment with Flask/Docker/AWS EC2 Telco Customer Churn WSL + Docker set up guide & Flask App and Dockerization notes Homework 5 AER Credit Card Data Solution Jupyter notebook
11-17 October 2022 Week 6: Decision Trees and Ensemble Learning Credit Scoring Visual overview of decision tree and ensemble models Homework 6 California Housing Prices Solution Jupyter Notebook
18-24 October 2022 Week 7: Production-ready ML with BentoML/AWS Fargate Credit Scoring Setting up and serving bentoML with WSL Homework 7 Credit Scoring Solution Jupyter Notebook
25 October - 7 November 2022 Mids Week: Do your own project --- Detailed Instructions Evaluation Criteria Traffic Violation Dataset Detailed descrition of project and instructions to reproduce
8-21 November 2022 Week 8: Deep Learning / CNN Clothing Dataset (small) Installing tensorflow + Connecting Github, VSCode and Saturn Cloud Homework 8 Dino or Dragon Solution Jupyter Notebook
22-28 November 2022 Week 9: tflite/Serverless with AWS Lambda Clothing dataset Overview Homework 9 Dino or Dragon Solution Jupyter Notebook
29 November-5 December 2022 Week 10: TF Serving/ Kubernetes Clothing dataset TBA Homework 10 Credit Scoring Solution Jupyter Notebook