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For 16 weeks, while you learn the theory of machine learning, you will be working with your team to build exciting projects.
NOTE: After you register, you must take the prerequisite courses below. We will send another form for applicant to upload a proof that they have taken the courses.

Prerequisite Courses for this cohort:
Udacity - Intro to Python
Udacity - Intro to Statistics
Udacity - Statistics
Udacity - Linear Algebra

Register

Deadline to register is 15th, June, 2021.

Schedule

Week 1

Introduction to Data Science

Resources: PDF (Data Science Course, CMU)

Practical

Data Science Notebook Frameworks

Week 2

Data Collection and Scraping

Resources: PDF (Data Science Course, CMU)

Practical

A web scraping task with basic introduction
Data Labelling Tools and Frameworks

Week 3

Relational Data

Resources: PDF (Data Science Course, CMU)

Practical

Intro to Pandas
Optimized computational Framework part 1 (Pandas related)

Week 4

Visualization and Data Exploration

Resources: PDF (Data Science Course, CMU)

Practical

Industrial Strength Visualization libraries

Week 5

Matrices, Vectors and Linear Algebra

Resources: PDF (Data Science Course, CMU)

Practical

Intro to numpy
Optimized computational Framework part 2 (Numpy related)

Week 6

Data Preprocessing

Resources: PDF (MLVU)

Practical

Outlier and Anomaly Detection

Week 7

Introduction to Machine Learning

Resources: PDF (Data Science Course, CMU); PDF (MLVU)

Practical

Intro to Sklearn

Week 8

Linear Models

Resources: PDF (Data Science Course, CMU); PDF (MLVU)

Practical

Week 9

Model Evaluation

Resources: PDF (MLVU)

Practical

Model and Data Versioning

Week 10

Nonlinear Models

Resources: PDF (Data Science Course, CMU); PDF (MLVU)

Practical

Week 11

Probabilistic Models

Resources: PDF (Data Science Course, CMU); PDF (MLVU)

Practical

Feature Engineering Automation

Week 12

Probabilistic Models (part 2)

Resources: PDF (Data Science Course, CMU)

Practical

Week 13

Tree Models

Resources: PDF (Data Science Course, CMU); PDF (MLVU)

Practical

Model Serving and Monitoring

Week 14

Unsupervised Learning

Resources: PDF (Data Science Course, CMU)

Practical

Week 15

Recommender Systems

Resources: PDF (Data Science Course, CMU)

Practical

Week 16

Tree Models

Project Presentation

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