ArewaDS Official Website: https://arewadatascience.github.io
Welcome to the Arewa Data Science Academy Python Programming Fellowship. This comprehensive, free program aims to equip aspiring data scientists and machine learning engineers with essential Python skills. A strong foundation in Python programming will significantly enhance your ability to learn data science and machine learning effectively.
This course is designed around hands-on, bite-sized exercises inspired by "Atomic Habits" by James Clear, to help you build strong Python habits. By completing daily tasks, you'll develop a deeper understanding of Python and apply your knowledge to real-world problems. Remember, consistency is key!
- 📘 ArewaDS Python for Beginners - Cohort 3.0
- 🗂 Table of Contents
- 🎉 Welcome to Cohort 3.0 ArewaDS Fellowship
- 🛠 Setup and Installation
- Setup Guide
- 🐍 Python Programming
Applications for Cohort 3.0 have now closed, but you can still access our materials for self-study. Stay updated on future cohorts by following us on social media and joining our Telegram group for regular updates and fellowship insights.
- 📺 Python Programming YouTube Playlist
- 🌐 Website: Arewa Data Science Official Website
- 📧 Email: arewadatascience@gmail.com
- Follow us on:
Whether you're just starting or deepening your skills, our fellowship offers a structured path to master Python fundamentals and beyond. The fellowship has three main stages:
- Stage 1: Python Programming - Essential Python skills for data science and machine learning (this course).
- Stage 2: Data Science - Data handling, from cleaning to analyzing.
- Stage 3: Machine Learning - Introduction to machine learning techniques and Scikit-learn.
To graduate from the Arewa Data Science and Machine Learning Fellowship, fellows must meet the following criteria:
- Completion of all three stages: Fellows must complete each stage to receive the ArewaDS Certificate.
- Assignments and Blog Posts: Submit all required assignments and a blog post on Medium. Posts must meet quality standards set by mentors.
- Attendance: Maintain a 90% attendance rate for weekly office hours (Saturday and Sunday).
- Capstone Project: Complete a capstone project that demonstrates your ability to apply learned skills to a real-world problem, approved by the ArewaDS Team.
However, for each stage we will provide certificate of completion.
Find the list of accepted fellows, mentor details, recording of the kickoff event, and the slides used during the presentation below.
| Component | Resource |
|---|---|
| Accepted Fellows Page | Visit the Accepted Fellows Page |
| Mentors | Check our Mentors list |
| Communication (Telegram) | How to use Arewa Data Science Telegram Group |
| Kickoff Recording | Link to Recording |
| Kickoff Slides | Link to Slides |
In this initial part, we’ll guide you through the essential tools needed for data science and machine learning, including installing VSCode, Jupyter Notebooks, Python virtual environments, Git for version control, GitHub for collaboration, Markdown, and creating a Medium blog post.
| Title | Resource | Recording | Mentor |
|---|---|---|---|
| Initial Setup | MacOS | Windows | Linux | Tutorial | Dr. Idris |
| Blogging using Medium | How to write Medium Article | Recording | Lukman |
| Basic Command Line Operations | CommandLine | Recording1| Recording2 | Dr. Idris | Falalu |
| Setup Git and GitHub | Git/GitHub | Recording1 | Recording2 | Dr. Idris | Falalu |
| Python Virtual Environments | Virtual Environment | Recording | Dr. Shamsuddeen |
| VSCode for Data Science | VSCode for DS | Recording | Dr. Shamsuddeen |
| Introduction to Markdown | Markdown | Recording | Dr. Shamsuddeen |
| Customizing GitHub Profile | Customizing Profile | Recording | Lukman |
| Google Colab | Google Colab | Recording | Dr. Idris |
| Assignment Name | Link to Assignment |
|---|---|
| Getting Started with Medium | Getting Started with Medium |
| GitHub Fundamentals | GitHub Fundamentals Assignment |
| GitHub Profile | Customize your Proile |
- Reference Book: Python Crash Course, 3rd Edition: A Hands-On, Project-Based Introduction to Programming
- Download the book here
| Week | Day | Topic | Session Recording | Mentor |
|---|---|---|---|---|
| 1 | Saturday | Getting Started (Introduction to Python, setting up the environment, running the first program). | Recording | Dr. Shamsuddeen |
| Sunday | Variables and Simple Data Types (Variables, data types, input/output). | - | - | |
| 2 | Saturday | Introducing Lists (Creating and accessing lists, modifying lists). | - | - |
| Sunday | Working with Lists (Looping through lists, modifying elements). | - | - | |
| 3 | Saturday | if Statements (Conditional tests, if-elif-else structures, boolean expressions). |
- | - |
| Sunday | Dictionaries (Creating and using dictionaries, basic operations, looping through dictionaries). | - | - | |
| 4 | Saturday | User Input and while Loops (Handling user input, while loops, break and continue statements). |
- | - |
| Sunday | Functions (Defining functions, arguments, return values, and passing lists to functions). | - | - | |
| 5 | Saturday | Classes (Defining classes, attributes, methods, and working with objects). | - | - |
| Sunday | Continuation (Inheritance and more complex class structures with exercises). | - | - | |
| 6 | Saturday | Files and Exceptions (Reading/writing files, basic file operations). | - | - |
| Sunday | Testing Your Code (Introduction to unit testing, writing tests for functions and classes). | - | - | |
| 7 | Saturday | NumPy Introduction (Creating arrays, basic operations, mathematical computations). | - | - |
| Sunday | Advanced NumPy (Array indexing, slicing, reshaping, and hands-on exercises). | - | - | |
| 8 | Saturday | Pandas Basics (Understanding Series and DataFrames, data loading). | - | - |
| Sunday | Advanced Pandas (Data cleaning, exploratory data analysis, and practice with real-world datasets). | - | - |
| Project | Project Title | Description |
|---|---|---|
| 4 | Generating Data | Work on generating and visualizing data using various Python libraries. |
| 5 | Downloading Data | Create a project focused on downloading, processing, and visualizing data. |
| 6 | Working with APIs | Integrate data from APIs and develop a project that uses external data sources. |
Each student must complete all the project in this course
We’re excited to have you on board and can’t wait to see all the amazing things you’ll accomplish!