This post has been republished via RSS; it originally appeared at: New blog articles in Microsoft Tech Community.
Thank you for signing up to the 30 days of learning. In this post, I will cover what you can expect during the entire period of the Data Science and Machine Learning track. But first, make sure you watch and complete the onboarding tasks at: https://aka.ms/30DLOnboardingRecap
In this track we will go from understanding the Python language to working with real life data and finally creating Machine Learning models both on Azure and in Python. The main role is understanding our data and using the knowledge to make decisions such as clustering Nigerian music based on their 'danceability' score, 'acousticness', loudness, 'speechiness', popularity and energy.
Main Onboarding tasks:
- Sign up for the Cloud Skills challenge: https://aka.ms/30DLDataScienceAndML
- Create and activate your GitHub Account: https://aka.ms/30DLGitHubSessionRecap
- Get Started with Azure for Students: https://aka.ms/30DLAzure4StudentRecap
- Set up Your Local environment: https://youtu.be/6pMvovj7KbE
- From GitHub to Visual Studio: https://youtu.be/Zxs1eK2acLk
The Curriculum:
- Python for Beginners: https://aka.ms/py4beginners
- Data Science for Beginners: https://aka.ms/ds4beginners
- Machine Learning for Beginners: https://aka.ms/ml4beginners
- Student hub: http://aka.ms/learnstudent
Below is the complete schedule for the program:
Day |
Date |
Topic |
Outcome |
Main content |
Other Resources |
Monday |
13-Jun |
Getting Started with Python |
Get started with Python! |
https://aka.ms/py4beginners - module 1 to 5 |
Reactor video: https://youtu.be/IY90FdFuxVI |
Tuesday |
14-Jun |
Python Basics: Boolean | strings | operations | list | loops | dictionaries | functions |
Write your first program in Python |
https://aka.ms/py4beginners - module 5 -10 |
|
Wednesday |
15-Jun |
Data Preparation + Introduction to Data Science |
Defining Data Science and what you can do with Data. |
https://aka.ms/ds4beginners - lessons 7 and 8 |
Reactor video: https://www.youtube.com/watch?v=xKIm02254SQ |
Thursday |
16-Jun |
Data Visualization Part 1 |
Learn how to use Matplotlib to visualize bird data :duck: |
https://aka.ms/ds4beginners - lessons 9 and 10 |
|
Friday |
17-Jun |
Data Visualization Part 2 |
Visualizing discrete and grouped percentages. |
https://aka.ms/ds4beginners - lessons 11 and 12 |
|
Saturday |
18-Jun |
General Track - Recap for the Week |
An hour session to run through all the learning for the week and also answer questions |
An hour session to run through all the learning for the week and answer questions |
|
Monday |
20-Jun |
Analyzing your Data |
This phase of the data science lifecycle focuses on techniques to analyze data. |
https://aka.ms/ds4beginners - lessons 14 and 15 |
|
Tuesday |
21-Jun |
Data Science in the Cloud |
This series of lessons introduces data science in the cloud and its benefits. |
https://aka.ms/ds4beginners - lessons 17 to 19 |
|
Wednesday |
22-Jun |
Techniques for Machine Learning + Intro to ML |
Learn the basic concepts behind machine learning |
https://aka.ms/ml4beginners - lessons 1, 3 and 4 |
|
Thursday |
23-Jun |
Regression part 1 |
Get started with Python and Scikit-learn for regression models |
https://aka.ms/ml4beginners - lessons 5 and 6 |
|
Friday |
24-Jun |
Regression part 2 |
Build linear and polynomial regression models |
https://aka.ms/ml4beginners - lessons 7 and 8 |
|
Saturday |
25-Jun |
General Track - Recap for the Week |
|
An hour session to run through all the learning for the week and also answer questions |
|
Monday |
27-Jun |
Deploy Your ML Model Using Flask Framework |
Build a web app to use your trained model |
https://aka.ms/ml4beginners - lesson 9 |
|
Tuesday |
28-Jun |
Classification |
Clean, prep, and visualize your data; introduction to classification |
https://aka.ms/ml4beginners - lessons 10 - 13 |
|
Wednesday |
29-Jun |
Introduction to Clustering |
Build a recommender web app using your model |
https://aka.ms/ml4beginners - lessons 14 and 15 |
|
Thursday |
30-Jun |
Time Series forecasting in action |
Time series forecasting with ARIMA |
https://aka.ms/ml4beginners - lesson 21 and 22 |
|
Friday |
1-Jul |
Introduction to natural language processing |
Learn the basics about NLP by building a simple bot |
https://aka.ms/ml4beginners - lesson 16 and 17
|
|
Saturday |
2-Jul |
General Track - Recap for the Week |
An hour session to run through all the learning for the week and also answer questions |
An hour session to run through all the learning for the week and also answer questions |
|
Monday |
4-Jul |
Machine Learning on Azure: ML Designer and AutoML |
Deploying models with Azure Machine Learning Studio. |
Create a Regression Model with Azure Machine Learning designer - Learn | Microsoft Docs and Use automated machine learning in Azure Machine Learning - Learn | Microsoft Docs |
|
Tuesday |
5-Jul |
Capstone project |
You are expected to work on a project that will help them demonstrate all the things they have learnt during the program with proper documentation on GitHub |
|
|
Wednesday |
6-Jul |
Capstone project |
|
|
|
Thursday |
7-Jul |
Capstone project |
|
|
|
Friday |
8-Jul |
Capstone project |
|
|
|
Saturday |
9-Jul |
General Track - Moving on from Here |
|
|
|
Sunday |
10-Jul |
Catch Up and Share Your Learning |
|
|
|
Monday |
11-Jul |
Tidy Up your GitHub and LinkedIn Profile |
|
You should be able to have updated LinkedIn Profile and GitHub Profile with their projects well documented |
|
Tuesday |
12-Jul |
Graduation |
|
Graduation |
|