Solutions on Practical Data Science Specialization

Access all courses in the Coursera Practical Data Science Specialization Specialization offered by deeplearning.ai.

This repo contains the SOLUTIONS of exercises/labs to achieve the badge.

Course keynotes and solutions of related quizzes, assignments

Practical Data Science Specialization on Coursera contains three courses:

1. Course 1: Analyze Datasets and Train ML Models using AutoML

Week 1:

• [x] Practice Quiz: Week 1.

• [x] Graded External Tool: Register and visualize dataset.

Week 2:

• [x] Practice Quiz: Week 2.

• [x] Graded External Tool: Detect data bias with Amazon SageMaker Clarify.

Week 3:

• [x] Practice Quiz: Week 3.

• [x] Graded External Tool: Train a model with Amazon SageMaker Autopilot.

Week 4:

• [x] Practice Quiz: Week 4.

• [x] Graded External Tool: Train a text classifier using Amazon SageMaker BlazingText built-in algorithm.

2. Course 2: Build, Train, and Deploy ML Pipelines using BERT

Week 1

• [x] Practice Quiz: Week 1.

• [x] Graded External Tool: Feature transformation with Amazon SageMaker processing job and Feature Store.

Week 2

• [x] Practice Quiz: Week 2.

• [x] Graded External Tool: Train a review classifier with BERT and Amazon SageMaker.

Week 3

• [x] Practice Quiz: Week 3.

• [x] Graded External Tool: SageMaker pipelines to train a BERT-Based text classifier.

3. Course 3: Optimize ML Models and Deploy Human-in-the-Loop Pipelines

Week 1

• [x] Practice Quiz: Week 1.

• [x] Graded External Tool: Optimize models using Automatic Model Tuning.

Week 2

• [x] Practice Quiz: Week 2.

• [x] Graded External Tool: A/B testing, traffic shifting and autoscaling.

Week 3

• [x] Practice Quiz: Week 3.

• [x] Graded External Tool: Data labeling and human-in-the-loop pipelines with Amazon Augmented AI (A2I).

Disclaimer

The solutions here are ONLY FOR REFERENCE to guide you if you get stuck somewhere. Highly recommended to try out the quizzes and assignments yourselves first before referring to the solutions here.

Feel free to discuss further with me on .