
1.1. Why here and now?
1.2. Key Concepts of Jupyter Notebook
2.1. Variables and data types
2.2. Basic Arithmetic Operations
2.3. Type Casting
2.4. Basic String Operations
2.5. Summary
3.1. Lists
3.2. Tuples
3.3. Dictionaries
3.4. Sets
3.5. Summary
4.1. Conditional Statements
4.2. Looping Statements - For Loop
4.3. Looping Statements - While Loops
4.4. Summary
5.1. Functions
5.2. Modules
5.3. Summary
6.1. Arrays: Creation, Indexing, and Slicing
6.2. Basic Operations: Array Arithmetic and Broadcasting
6.3. Useful Functions
6.4. Summary
7.1. DataFrames: Creation, Indexing, and Slicing
7.2. Basic Operations: Adding Columns, Filtering, and Aggregation
7.3. Useful Functions
7.4. Summary
8.1. Basic Plotting
8.2. Customization
8.3. Advanced Plotting
8.4. Summary
Here comes a complete notebook with exercises and solutions for each section in three versions: class-version, detailed solutions, and an empty version for you to practice the final exercises.
Are you eager to learn Python but overwhelmed by the endless hours of tutorials packed with excess information? After nearly a decade of hands-on experience in data science with Python, I've crafted my first introductory course to focus on what truly matters. This streamlined, no-nonsense course covers only the essentials useful on a daily basis, ensuring you gain practical, relevant knowledge without the fluff. It's a solid foundation to jump-start your career in Python-based analytics and build on in the long run.
This course covers seven core topics and includes hands-on exercises to test your skills. While the notebook topics are generic and aimed at giving you a good foundation for further deep dives, I have tailored the examples to the geospatial analytics field wherever possible. Don't worry if you're not into GIS—you'll still be able to follow along and learn a lot. However, if you are into GIS, these examples will be particularly relevant and familiar. Check out the outline below!
Benefits
Here are the main benefits of this course, making it an excellent choice for anyone planning to get on-board with Python:
Focused Content: Concentrates on essential Python skills without overwhelming you with unnecessary information.
Practical Application: Emphasizes practical, daily-use knowledge, making it highly relevant for real-world scenarios.
Geospatial Analytics Examples: Provides examples from the geospatial analytics field, enhancing learning for those interested in GIS.
Final Exercises: Includes a set of final exercises to test and reinforce your skills.
Expert Instruction: Taught by an experienced data scientist with nearly a decade of hands-on Python experience.
No Fluff: A streamlined, no-nonsense approach ensures efficient learning.
Foundation for Growth: Offers a solid foundation you can build on for more advanced Python and data science topics.
Bonus Cheat Sheets: Included for every section as a reference guide — these cover additional topics beyond the course scope for your further learning.
Accessible to All: Designed to be approachable even if you're not into GIS, ensuring broad applicability.
What you get
The pre-recorded course comes with multiple videos and Jupyter Notebooks:
9 Videos: Totaling about 200 minutes of content
8 Chapter-level Jupyter Notebooks: One for each topic chapter
3 Exercise Notebooks: Class version, detailed solutions, and an empty version for you to practice the final exercises
Summary Notebook: A comprehensive notebook combining all chapters