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:
The Curriculum:
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: |
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 |
Self study on the given modules. |
Wednesday |
15-Jun |
Data Preparation + Introduction to Data Science |
Defining Data Science and what you can do with Data. |
https://aka.ms/ds4beginners do lessons 7 and 8. |
Reactor video: https://aka.ms/analyseData Data - |
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 |
Follow up video: https://aka.ms/manipulateData |
Friday |
17-Jun |
Data Visualization Part 2 |
Visualizing discrete and grouped percentages. |
https://aka.ms/ds4beginners - lessons 11 and 12 |
Video: https://aka.ms/data-viz Data: https://aka.ms/birdsData |
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 |
Task: go through the instructions on the two lessons and using what you have learnt, analyze and visualize https://aka.ms/spamdataset. Share your work on Discord and Twitter once done. |
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 |
Video Recording: https://aka.ms/30DL-dscloud |
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 |
Introduction to regression: https://aka.ms/30DL-regression Resources: https://aka.ms/30DL-RegressionRe |
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 |
Data: https://aka.ms/30DL-ufodata Live session: https://aka.ms/30DL-deploymodels Resources: https://aka.ms/30DL-WebDeployRe |
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 |
Live session: https://aka.ms/30DL-Clustering Resources: https://aka.ms/30DL-ClusteringRe |
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: Custom Vision |
Deploying models with Custom Vision AI. |
Create a Regression Model with Azure Machine Learning designer - Learn | Microsoft Docs and Use automated machine learning in Azure Machine Learning - Learn | Microsoft Docs |
Live session: https://aka.ms/30DL-MLSumProject |
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 |
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Wednesday |
6-Jul |
Capstone project |
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Thursday |
7-Jul |
Capstone project |
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Friday |
8-Jul |
Capstone project |
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Saturday |
9-Jul |
General Track - Moving on from Here |
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Sunday |
10-Jul |
Catch Up and Share Your Learning |
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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 |
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Graduation |
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