Data Analysis Curriculum

Data Analysis

This curriculum is offered in these locations and formats

Women+ STL KC Part-Time In-Person Virtual
Our Data Analysis course trains learners to use data to answer business questions and inform decision-making. LaunchCoders utilize Python, SQL, Google Sheets, and Tableau to clean, profile, model and visualize data, and to report back findings in a manner consumable by stakeholders. This class is great for someone who is interested in researching, story-telling with data, and communicating insights in engaging ways. People with data analysis skills can query and analyze data to answer business questions, predict performance, and create data-driven recommendations to improve outcomes.

What You Need to Know

Students will need access to a laptop to participate in the course. While LaunchCode does not provide laptops to people who are in the process of applying, we can explore resources with our enrolled learners if they are unable to replace a laptop that stops functioning during class. (For affordable laptop and wifi access, we recommend looking into PCS FOR PEOPLE, CONNECT ALL, and the AFFORDABLE CONNECTIVITY PROGRAM). Chromebooks and tablets will not be sufficient for use in this course. If you own a PC, you must have Windows 10 or a more recent operating system. It should have at least 4 GB RAM, though 8 GB is strongly recommended. If you own a Mac, it should run the latest operating system. Please apply all system upgrades before coming to class.

Although this course is free, it is challenging and requires commitment. Outside of class, you are expected to spend 15-20 hours doing readings, watching videos, working on practice problems, and completing assignments. No previous coding experience is required for this class.

Please note the blue tags in each available course below to determine which course is offered in the format and location you wish to apply to.

You Will Need

  • A laptop computer running Windows 10 or latest Mac OS (no Chromebooks, Linux OS, or tablets)
  • Reliable access to the internet (local public libraries provide free wifi on location, and may also offer reservable hotspots) 
  • To attend instructor-led class sessions each week
  • For part-time classes, 15-20 hours outside of class time each week to work on class material

Main Topics Covered

  • Spreadsheet Basics
  • Exploring Business Issues 
  • Asking Questions of Data 
  • Data Discovery
  • Exploratory Data Analysis in Python and T-SQL 
  • Cleaning Data in Python and T-SQL
  • Creating Visualizations in Tableau 
  • Coding Fundamentals in Python
  • Data Cleaning, Manipulation and Visualization in Python
  • Introduction to Statistics and Data Modeling
  • Career readiness skills, including resume review and behavioral and technical interview prep

Jobs This Can Lead To

  • Data Analyst
  • Business Analyst 
  • Data Scientist (Additional training required)

Special Course Designations

We believe that these opportunities should be available to anyone with the passion, drive, and aptitude to learn them. In order to support increasing diversity within the field of technology, we offer some classes specifically targeted toward groups of individuals who are underrepresented in the field of technology. For example, courses marked with the audience tag Women+ are held specifically for women and people of marginalized genders.

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