Data Science

Become a Data Science professional in just 12 (or 24) weeks!

Dive into the world of Data Science, data modeling, machine learning, and more in this advanced Deep Dive Coding Bootcamp. You will learn to solve critical business problems within your domain of expertise with new skills in programming, modeling, and data analysis. Students will work on labs and projects to build and maintain data models. Graduates will be able to design and implement a real-world model producing actionable information.

Data science and AI skills have been identified by the World Economic Forum as an emerging prospect in the future of work, with the number of job opportunities in this field expected to grow by 450,000 from 2020-2022. Glassdoor estimates that Data Scientists are well compensated, with an average salary in Albuquerque of $75-$125K, and up to $140K nationwide.

Full-time bootcamp schedule

January 2021
Dates: January 11 – April 2
Times: Mondays-Thursdays 8am-5pm
Application Deadline: December 11, 2020

Part-time bootcamp schedule

January 2021
Dates: January  8 – June 18
Times: Fridays 8am-5pm & 8 hours asynchronous online throughout week. Time outside of class could be more than 8 hours depending on prior experience and project difficulty.
Application Deadline: December 11, 2020

Learn the Technology

We’ll teach you the languages, tools, and techniques you’ll be using as a data scientists in the real world. This bootcamp focuses on…

• Critical thinking and project selection
• Python and open source libraries for data science
• Visualization tools to explore data sets for further processing
• Data wrangling techniques to prepare and refine raw sets
• SQL queries and useful syntax for access to data
• Machine learning algorithms
• Cloud based Jupyter notebooks and other deployment tools
• GITHUB, Slack, Agile development tools

Pre-requisites

• A data scientist has a multidisciplinary blend of skills. It’s much more than knowing how to program or understanding statistics. Knowledge of a business domain is helpful to solve business problems with data science. As such, we recommend at least 2-5 years of relevant business experience area well enough to:
  • Solve significant problems in their area
  • Write papers or blog posts about their work
  • Speak about their work at a conference of their peers
  • Recognize results in a model that are either invalid or trivial (this is the important one for our purposes!)
• Basic knowledge of statistical concepts, probability distributions, and linear algebra will be required. To meet this pre-requisite, it is required that you take our short assessment on linear algebra and probability & statistics.

These resources can help you review for the assessments:
Probability/Statistics: Link
Linear Algebra: Link – Andrew Ng – Lectures 3.1-3.6

• Coding experience will be required. If you do not have coding experience, contact us for resources to help you get up to speed.

Some exceptions to pre-reqs can be made. Apply if you’re interested, and we can discuss!

Testimonial

Program

Pre-bootcamp (before the program starts)
Pre-work will be assigned to you before the bootcamp starts. All the resources used in the pre-work are accessible online or will be provided to you. During pre-work, you will set up your system accounts, meet with the Bootcamp Success Manager, prep your software environment, work through multiple tutorials on DataCamp*, and will make other final preparations. Pre-work is mandatory and must be completed prior to orientation, which is generally a few days before bootcamp begins. The sooner you start and the more time you spend on your pre-work, the more prepared you’ll be. We recommend that you give yourself at least a month to complete this work prior to the start of the bootcamp.

*This class is supported by DataCamp, the most intuitive learning platform for data science. Learn R, Python and SQL the way you learn best through a combination of short expert videos and hands-on-the-keyboard exercises. Take over 100+ courses by expert instructors on topics such as importing data, data visualization or machine learning and learn faster through immediate and personalized feedback on every exercise.

Data Science Fundamentals (Weeks 1-4)

• Learn project selection and use case development – critical thinking
• Overview of the Python computer language
• Learn and practice cloud-based processing using Jupyter notebooks
• Learn about data sources and collection methods
• Conduct extensive exploratory data analysis
• Survey of data visualization tools
• Practice using the probability and statistics needed by Data Scientists

Statistical and Machine Learning (Weeks 5-9)

• Learn and practice database queries with SQL
• Clean up dirty data sets (data wrangling)
• Learn and practice regression techniques (linear, logistic, regularized)
• Supervised learning techniques: K-nearest neighbors, decision trees, random forests, and boosting
• Unsupervised learning techniques: Clustering, dimensionality reduction
• Deep learning: Image identification using Convolutional Neural Networks
• Learn performance improvement techniques: regularization, avoiding over-fitting, data augmentation
• Text processing techniques: Natural Language Processing

Capstone Project (Weeks 10-12)

• Immerse yourself in your team capstone project
• Create clean, functional, and documented code for your Github resume
• Demonstrate your team capstone projects to employers, staffing agencies and others in the tech community

Cost

The total bootcamp tuition is $9,995.

Participants receiving third-party funding may not have to pay a deposit or any tuition. Learn more about financial assistance and the payment process for the bootcamp. *Prices subject to change.

Reserve Your Seat Now: A $1,500 non-refundable deposit is required prior to the application deadline in order to reserve your seat. The remaining course fees must be paid in full by the application deadline.

Instructor

Cliff Lewis
Lead Instructor

Cliff Lewis received his Ph.D. in Physics with specialization in Chaos Theory from the University of California, San Diego. He held the position of Assistant Vice President at Science Applications International Corporation where he managed data-intensive technology programs for the DoD and DHS in the areas of biotechnology, 3-D tomography, data science, and signal processing. He started Think Tank Analytics in 2011 and provides clients with successful product development in many different areas of data science, including Wearables and Personalized medicine, Predictive Analytics, Fitness Analytics, and Data-Intensive Mobile App Development for smartphones.

Kyla Bendt
Assistant Instructor

Kyla developed her passion for teaching while working as a math and science tutor in college. She went on to spend 12 years working in many different roles at a GIS software company. Looking to add to her skills and interested in trying something new, she took Deep Dive’s Fullstack Web Development Bootcamp in 2019. When Deep Dive announced a new Data Science Bootcamp, she jumped at the opportunity to combine her interests in teaching, coding and math as an assistant instructor.
Kyla has an Associate’s degree in General Science from San Juan Community College in Farmington and a Bachelor’s degree in Mathematics from New Mexico Tech in Socorro. She likes mountain biking, baking bread and going over the ABC’s of web development with her young son.