Online Data Analytics Bootcamp

The bootcamp itself is structured into 18 learning units which include: 

1. Program Overview.

2. Structured Foundations.

3. Your Job Search Strategy.

4. Microsoft Excel for Business Analytics.

5. Financial Analysis.

6. Effective Networking: Building Your Network.

7. Economics for Data Analysis.

8. Statistics for Data Analysis.

9. Informational Interviews.

10. Visualization Tools.

11. The Art of Storytelling.

12. Find the Right Job Title and Companies.

13. Data Connectivity.

14. Preparing for and Getting Interviews.

15. Data Analysis in Python.

16. Capstone.

17. Effective Interviewing for Data Analysts.

18. Bootcamp Conclusion and Congrats!

As a data analyst, you help shape a company's strategic or financial goals. Working with your mentor, you'll choose a previously determined data set or find an alternative data set that interests you. The capstone is the course's final project, so you'll utilize everything you've learned as a future business-oriented data analyst. Quick highlights include:

• Create and state your hypothesis to be proven or disproven.

• Draw a data hierarchy map and extract data from relational databases using SQL.

• Organize and clean the data.

• Use advanced visualization tools you've mastered to create and present the project.

Offered as a supplemental option, career units are designed to help you get a job upon completing the Data Analytics Bootcamp at Stony Brook University. You'll work with a career coach on a job search strategy, build your resume, practice interviewing techniques and learn how to network.

Bootcamps can be a great way to gain the skills you need in order to start a career in data analytics, especially if you want to keep tuition costs low and move into a new career within months rather than years. However, not all programs are created equal, so it’s important to do your research before enrolling. Some things to look for when choosing a data analytics bootcamp include an up-to-date curriculum, what student support will be available, and how the bootcamp will fit into your life.

The Stony Brook University's Data Analytics Bootcamp will have you job ready in as little as six months. It’s 100% online, so you don’t have to put your full-time job on hold. You’ll have the support of a whole team, including your industry mentor. When you graduate, you’ll have earned a credential from a leading university and you’ll have the portfolio to prove your skills. 

Data analytics is the process of examining large data sets to uncover hidden patterns, correlations and trends. It's a powerful tool for understanding what is happening within your business, and it can help you make more informed decisions about where to allocate your resources.

Data analytics can be used to improve marketing campaigns, detect fraudulent activity, identify customer needs and preferences and optimize operations. The possibilities are endless, and the benefits are clear.

Data analysts are in high demand, and it's only going to continue to grow in the coming years. Companies are collecting more and more data every day, and they need people who can help make sense of it all.

A data analyst gathers, cleans and organizes data to identify trends and relationships. They then use this information to make informed business decisions.

Some of the most common tasks of a data analyst include: extracting data from various sources, cleaning and transforming data, identifying patterns and trends, developing models to forecast future trends and presenting findings to stakeholders.

Data analysts must be able to work with large volumes of data, as well as with different types of data (including unstructured data). They must also be able to think critically and analytically to derive insights from complex datasets.

It can take months or years to build all of the skills needed to become a data analyst, but a program like the Stony Brook University's Data Analytics Bootcamp can help speed that process up. With curated curriculum and the support of your 1-on-1 expert data analytics mentor, you’ll learn these skills more quickly. 

If you have a background in programming or statistics, you'll be able to learn the necessary skills for data analysis more quickly. But even if you're starting from scratch, with some focused effort you can become proficient in data analysis.

The median advertised salary for data analysts in New York is $77,568 according to Lightcast (Oct 2022 - Sep 2023; 0-3 years minimum experience required. New York.) Salary can range depending on role, sector, years of experience and location. 

Foundationally, you need to develop the ability to collect, organize and analyze data to work in data analytics. This involves having a basic understanding of statistics and being able to use software to extract insights from data.

You also need strong problem-solving skills. Data analytics is all about identifying patterns and trends in data and coming up with hypotheses about what they mean.

Verbal and written communication skills are important too, as you will often need to communicate your findings to others clearly and concisely. The adoption of your recommendations is reliant upon your communication skills.