🗓️ Week 03 - Computational Thinking and Programming

2023/24 Autumn Term

Author

This week, we will keep exploring the Computer Science side of Data Science. We will discuss how to approach problems the computational way, and then we will discuss what algorithms are and practice the art of creating them.

We will briefly touch upon the R vs Python debate, and we will introduce you to some of the essential tools used by data scientists to organise their code.

👨‍🏫 Lecture Slides

Either click on the slide area below or click here to view it in fullscreen. Use your keypad to navigate the slides. You can also find a PDF version on Moodle.

🎥 Looking for lecture recordings? You can only find those on Moodle.

🐍 Exploratory data analysis demonstration

You will find the content of the exploratory data analysis demonstration that was shown in the second part of this week’s lecture on this page.

✍️ Coursework

This week, there is no coursework or formative strictly speaking (you should start working on those week 4 presentations!) but I would encourage you to take some time to learn a bit of Python. Your programming skills will not be assessed in this course (but they are central to data science!), but this is the perfect opportunity to learn the basics and see how you feel about it.

After accessing Nuvolos or Google Colab as per the lab/lecture instructions, try the following:

running the code provided in the class. See if you can understand what it does.
learn the basics of Python. Check out this tutorial from Google or this Python for Beginners guide from the Python Software Foundation. Real Python (2023) is also a good resource to start with.
start getting a feel for pandas i.e the Python library most used for data science purpose here.

Ready for a more serious try? LSE DSI students can get a premium license to a Dataquest course in Python for data science. Join the Dataquest: introduction to Python for data science Moodle page and read the instructions carefully for how to gain access.

📚 Recommended Reading

Check the end of slides for the list of references cited in the lecture.
Check the 📔 Syllabus for this week’s complete list of indicative and recommended readings.

📟 Communication

Post your reflections, questions, and links on Slack’s #topic-programming channel.

References

Real Python. 2023. “Introduction to Python.” Real Python. https://realpython.com/learning-paths/python3-introduction/.