Data Science Training Curriculum
From February - April 2022, all Launch candidates have completed a series of introductory data science workshops.

For the first 3 weeks of the summer program, all candidates will complete 150+ hours of skills training in data science. See an overview of what they will learn below. All training is completed before day 1 of their internships.

Note: due to the fact that most training occurs in May & June, candidates you interview may not be able to answer detailed technical questions about all of these concepts yet.

Semester Intro Training (February - April 2022)
The semester's introductory training is focused on building and refining foundational programming and data management skills in Python and the pandas library. The first session catered exclusively to those without prior Python experience, and covered fundamental syntax and programming concepts, while the latter two sessions focused on teaching students the ins and outs of the pandas library.

While many would've said they had pandas experience before these sessions, we focused on teaching them the rules and interface of the library so that they can perform their analyses correctly the first time, improving iteration speed through eliminating a ton of trial-and-error.

Week 1 of Summer Training (May 23 - May 27)
Week 1 is focused on the 'business analytics' facet of data science, which we understand is a focus of many internships. We'll start the week by extending their pandas knowledge into more complex aggregations and custom analyses, then move on to data visualization. We'll cover a bit of necessary theory to iron out many of the common "amateur" data visualization mistakes (overusing pies, unreadable scatter plots, semantically meaningless rainbow color scales) before moving on to teaching data visualization fundamentals in a few of the most common industry-standard code and low-code frameworks, focusing on Python plotting libraries and Tableau.

Week 2 of Summer Training (May 30 - June 3)
Week 2 focuses on all of the essential additional skills necessary to contribute meaningfully as a data scientist at a tech company. We'll start by teaching the basics of the bash terminal, then move on to practice technical collaboration workflows in GitHub, including branching, pull requests, and code reviews. In the second half of the week, we'll discuss common database architectures, the difference between SQL and NoSQL databases, and give the students time to learn the basic SQL syntax before throwing them into the project.

Week 3 of Summer Training (June 6 - 10)
While not every internship will require students to be directly involved with machine learning, many will, and all of them should be able to speak the language. We will teach the basic theory behind predictive modeling, introduce a few simple models, practice their implementation through the sklearn API, and address important DEI issues raised by machine learning, especially deep learning.

Throughout all of Launch, professionalism is taught with a special focus on communication skills (emails, standups, code-walkthroughs, presentations) as well as organization and planning skills.

    Internships begin on Monday, June 13th 2022.