This class is live online (i.e. synchronous).
Are you curious about data analytics?
Have you started exploring data on your own but want to find out if you’re on the right track? Are you considering a career change and want to see what working on an analytics project is like? Would basic knowledge of analytics and tools like using Python in a Jupyter Notebook be helpful in your current career? If you are looking for a hands-on introduction to data analytics and want to demystify analytics and data science, the Data Analytics Jumpstart was created for you.
Is this course for you?
What will the course cover?
The Data Analytics Workflow
You will learn about the data analytics workflow and have hands-on exposure to many parts of it, including collecting, cleaning, merging data, exploratory data analysis, communicating, visualizing, and sharing findings.
PythonLearn the basics of data analysis with Python, a widely used programming language in analytics. This course will introduce you to a few analytics libraries that are useful for data analytics and data visualization, e.g. pandas, matplotlib, and seaborn.
SQLUse Structured Query Language to select data from a database.
Reproducible Workflow with Jupyter NotebooksJupyter Notebooks are widely used by data analysts and data scientists to document and share their analysis work. Learn to use markdown and code in combination to document and share your workflow. This adds transparency to your work and strengthens your analysis.
Analytics CareersLearn about the kinds of jobs that are available in data analysis and data science. Learn about the different types of analytics and how they are used in different domains to answer questions and solve problems.
Exploratory Data AnalysisLearn techniques for getting to know your data quickly, generating summary statistics and creating plots to show distributions, relationships between variables, and more.
Data Visualization & StorytellingYou will get practice communicating your analysis process and findings to non-technical audiences, an essential skill for data analysts and data scientists.
How will you learn the material?
What is required?
- Personal Laptop (No Chromebooks please. You will need at least 5GB of free hard drive space.)
- Must be 18+ years of age
- No prior technical training, analytics, or web development experience is required.
- Basic computer skills and proficiency. You should know how to use common applications, such as word processing, and have familiarity using the internet.
ScheduleSaturday, Tuesday, Thursday S: 9AM-2PM CT | T/Th: 6PM - 9PM CT
LocationThis class is live online (i.e. synchronous).
See Schedule Below
$500 credit toward any NSS bootcamp. (Only one $500 Jumpstart credit may be applied per bootcamp.)