Curated by Skillshare
5 Classes (9 hours 26 minutes)
- Materials
Internet connection, Replit.com, glitch.com, Google CoLab
- Final Product
Custom automation tools, practice problems with solutions, downloadable slides
- Level
Beginner
Coding 101: Python for Beginners
In this class, learn the basic concepts needed to start using code yourself, including data types, functions, and control logic. You'll finish the class having created a set of cool tools for automating common day-to-day tasks like an Email List Reformatter and Birthday Countdown Timer.
Learn How to Learn Coding Faster: Object-Oriented Programming in Python
This highly interactive class covers a must-know topic for every programmer: Object-Oriented Programming (OOP). At the end of the class you will have created a simple ice cream truck and household lights simulator using OOP concepts like classes and instances. You'll also learn how to keep code readable (abstraction), maintainable (inheritance), and flexible (mixins, composition).
Kick Butt in Coding Interviews: Data Structures in Python
Next up, explore another fundamental for programmers: data structures. In this class you'll learn how to analyze and understand algorithm “efficiency” using orders of growth analysis, as well as commonly-used data structures: stacks, queues, linked lists, trees, and hash maps. Plus, get in-depth practice questions and helpful interview tips if you plan to apply for programming jobs!
Artificial Intelligence for Beginners: Tools to Learn Machine Learning
Now it's time to advance from learning core concepts to exploring a real-world application of computer science: artificial intelligence. You'll learn what artificial intelligence is and how it relates to machine learning; build a Face Emotion Classifier to practice using machine learning concepts; and dig deep on concepts like linear regression, bias-variance, classification, regression, and featurization.
Data Science 101: Python Data Visualization for Beginners
Finally, learn one of the most powerful and exciting applications of Python: data visualization. In this class you'll learn how to turn a synthetic dataset of web traffic between two competing landing pages into a compelling visual story. The process and the skills you'll practice -- experimental design, data collection, and data analysis -- are applicable to countless scenarios you might encounter in your future work.
Congratulations! You’re All Done.
You did it! You’ve completed the full Learning Path. We can’t wait to see where these skills take you next.