Data Science and Analytics Bootcamp

Professional Development Course

In partnership with HackerU, the College of Professional and International Education (CPIE) at California State University, Long Beach (CSULB) offers a Data Science and Analytics Bootcamp with the goal of transforming learners with little or no experience into ready-to-hire data scientists in less than one year. This comprehensive curriculum teaches the most up-to-date skills and hands-on experience that employers look for in qualified data professionals, with instructors who are leading professionals in the industry.

Students utilize cutting-edge materials to engage in project-based learning, practicing real-world scenarios and developing the critical thinking necessary to succeed in the data science and analytics field. The immersive learning environment is designed for learners with a non-technical background to gain hands-on experience that can qualify them for entry-level positions.

No previous experience in tech is necessary. Students can start from scratch, learn the basics, and then progress to in-depth training topics. At the end of each program, HackerU provides comprehensive Career Services for assistance in job and internship placements.

To learn more about this program and to contact a consultant, visit Hacker U's Data Science and Analytics Bootcamp page.

Technical Requirements

Before enrolling, students should have the following :

  • Intel Core i7 Processor or newer
  • 16 GB of RAM
  • 500 GB hard drive
  • Dedicated GPU: NVIDIA GeForce 1050 GTI w/ 4GB VRAM (or better*) that supports CUDA**
  • A Windows PC with the latest operating system***
  • Second monitor is strongly recommended

*The dedicated graphics card listed above will likely not be used during the Introduction course, but will be used during the Extended course.

**CUDA only works with NVIDIA GPUs, and is used primarily for accelerating machine learning times. Some machine learning models will not perform well if the laptop or desktop does not have this.

*** A PC will work best for this program and is preferred; but a macOS is also possible.