SKILL LEVEL:
PREREQUISITES:
OVERVIEW:
TOPICS COVERED
JOBS THAT TYPICALLY USE OR REQUIRE THE CISSP:
SCHEDULE:
Data Science Immersive
Creating the next generation of Data Scientist
Our simple Data Analyst to Machine Modeler pathway ensures that students don’t need prior knowledge of any tricky math or stats. In this program, students will develop the building blocks to master today’s most in-demand industry tools.
Student experience

Our comprehensive course is 400 hours in duration and can be completed in two different schedules: 10 weeks from Mon to Fri between 9:00 AM – 6:00 PM, or 20 weeks from Mon to Fri between 9:00 AM – 1:00 PM.

Expert-Led Instruction That Gets You Job-Ready: Become a true data practitioner. Gain fluency in the field and collaborate with leading professionals through lectures, research exercises, and real-world client projects

Exclusive Access to Leaders in Data Science: Our course offers countless opportunities to learn and engage with data science professionals and technologists from around the world.

Gain a Valuable Professional Network: Transform and grow your career alongside peers (and potential collaborators) on campus and in our Connected Classroom. Discover all the different paths you can take with this in-demand knowledge and skill set from those who have walked the walk. The DA community is a priceless resource — just ask our alumni.

Course details

Modeling for Insights: Get acquainted to Modeling for insights through a well-rounded technical foundation which includes hands-on Structured Query Language labs, and then Model data using Data Analysis Expressions (DAX) using real-world examples that helps look at the reports in a different way i.e., with the correct model, the correct answer is always a simple one!

Modeling for Prediction: Automation with Machine Learning is the significant aspect of this module. Explore the data to generate hypotheses and intuition and communicate results through Analyzing and Visualizing data with Power BI, Data Shaping through Power Query, and Enterprise Business Process Automate using Power Platform and Azure Cognitive AI.

Scaling for Analytics: Scaling Analytics through the Auto ML – apply regression and classification techniques to power business forecasts and drive decision-making and strategy, Data Engineering through the transfer of Power Query and M-Language skills into Azure Data Factory (ADF) and build skills to troubleshoot underperforming queries and drifting Machine Learning models.

Project Capstone: This module serves as the capstone for the 9 weeks of learning through the integration of Data Science skills through a project focused on real-world open data. The learner may choose to work alone but preferably in a group of 2-3. In addition, support from staff is provided to tailor the data science process steps to develop a minimum viable data product. A learner is assessed on their problem hypothesis, statistical model, insights delivered through the use of the model, and flexibility of the model. The goal of this this module is to help a learner to develop an effective LinkedIn Profile, showcase a project portfolio, prepare for interviews by revisiting their capstone problem, and share capstone project results.

Certifications: By the end of this course you will have the skills needed to acquire Microsoft Azure Fundamentals (AZ-900), Power Platform Fundamentals (PL-900), Data Analyst Associate (DA-100), and Data Fundamentals (DP-900).

Data Analyst and Data Science Jobs: Equip yourself to succeed in a career such as a Database Developer, System Engineer, Database Administrator, Report Visualizer, Power BI Architect, Data Visualization Engineer, Power Query Developer, Cloud Engineer, and Applied Data Scientist.

Instructors

Our instructors represent the brightest professionals from companies like John Deere, Signify Health, Microsoft, Oracle and Amazon Web Services. They bring in-depth experience from the field to the classroom each day, providing invaluable insights into succeeding on the job.

Naveen Bannagani, Dallas, ‎Lead Data Science Instructor

Marcel Samuel, Dallas, Lead Data Science Immersive Instructor

Drew Minkin, Data Science Immersive Instructor

Career support

Strategy and Accountability: Our Career Services team works with you to individualize your path to a new career. Stay on track and motivated from the first day of class!

Resume Review: Learn how to design and tailor your resume to land the career you are looking for. Remember: every word counts.

LinkedIn Optimization: LinkedIn profiles are now mandatory extensions of our resumes. Setting up a thoughtful, well-written profile is the make or break for many inquiring employers. Using industry tips and tricks, we’ll work with you to spruce up yours.

Interview Preparation: Set up mock interviews to nail the real thing. Learn to develop effective interview strategies, get detailed feedback, and reduce stress before actual interviews.

Networking Opportunities: Learn how to navigate uncharted networking waters, tap into our expanding Divergence Alumni network, and watch your support and contacts grow!

Admission process
Step 1
Apply
Let's talk through it: your background, chosen path, weekday or weekend schedule, funding options, and more. Schedule an appointment with our Admissions Team.
Apply now
Step 2
Online Wookie Course
Curious folks, we will not make you wait to get started on your learning journey. You'll be enrolled from the get-go in either Data or Cyber Wookie. Each provides valuable resources to help our future data scientists or ethical hackers prep for the first day of class.
Step 3
Decision
Congrats! Your funding has been verified and you are accepted into the program. Be on the lookout for a personalized Acceptance Letter via e-mail. You can always call us at 833-DIVERGE
Step 4
Orientation
Experiencing first day jitters? Here's how we can help.
A week before your program starts, our Community Manager will get you onboarded to the learning platform, walk you through TWC enrollment paperwork, and connect you with future classmates.