Wrapping Up

After you've finished with the lessons for this course, this lesson will tell you where you can go from here.

What have you learned?

It's a good idea to reflect on all that you've learned in this course.

In the first part of this course, you learned how to create basic python projects, use basic programming data types, and draw objects on the screen using code.

Next, you learned how to take user input, create branching code with conditionals, and use complex data structures to create a hangman game.

Then, you learned how to use python's classes and lambda functions along with a user interface to create a Rock-Paper-Scissors game.

After that, you learned about data science concepts like data analysis and natural language processing along with file manipulation and NumPy to create even more complex programs.

Finally, you learned how to use Pandas and Matplotlib to manipulate and view dataframes and learned about uses of machine learning before creating a text classification program.

What comes next? If you want to expand your knowledge of concepts learned in this courses, you can check out the bonus lessons on creating a space shooter game, creating an advanced Rock-Paper-Scissors AI, or creating a text generation machine-learning model.

If you're looking to learn more beyond this courses, the next sections will help you understand where you can go from here.

Understanding a Subject Area

What do you want to learn more about? If you want to keep learning, it's important to pick topics that interest and inspire you to keep trying to write code even when there are difficult bugs to solve.


As living together with lots of different people gets more complicated, we need to use data to make sense of our society and our world. If you're interested in being a civics-minded data scientist, you can take publicly available datasets from sites such as Data.gov and use data analysis to identify and offer solutions to problems that impact millions of people.

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Science has its origins in directly observing experiences to understand the world around us. Scientists nowadays need data science skills to analyze enormous amounts of data to learn what the world has to tell us. You can use data sets like the USGS datasets to gain a better understanding of the world around us or the NASA datasets to understand the universe beyond earth.

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If you like to think about money, there are lots of opportunities to use machine learning and AI in the finance field. For example, you can use the python googlefinance api to get information about the stock market.

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Python Use Cases

Data Science Python Packages
In this course, you scratched the surface of the scikit-learn python package, but it can do more than just text classification. You can look at the scikit-learn examples to see other types of data analysis you can perform.

Interested in creating more procedural art? In this course, you learned how to use the turtle package to create art. If you want to delve more into natural language processing, the nltk package allows you to perform more in-depth analysis of words and sentences. If you're interested in music, packages like mingus can create music by using a python program.

Game Development
In this course, you made some basic games in python. Creating games can be very complicated, but using a framework like pygame can make the process easier.

Other Programming Languages

If you want to expand your knowledge beyond python, here are some other languages commonly used by data scientists.

R is a programming language used for data manipulation, calculation, and graphical display. It can be more challenging to learn than python, but because it is so focused on processing and viewing data it can sometimes be more powerful than python. You can learn more about R at the R-Project website.

In this course, you used data sources that came with python as well as spreadsheet files. In a real-world environment, you might need to access data stored in a database with a programming language like SQL. While you may not have your own database, you can still
learn how to code in SQL.


This course prepared you with the tools to create python programs, but where you go from here is up to you! For information about other courses offered by the Mason Game and Technology Academy, visit the MGTA website.