Deep Dive Data Science (Part-time)

Dive into the world of Data Science, data modeling, machine learning, and more in this advanced Deep Dive Coding Bootcamp

This life-changing, award-winning and cost-efficient program provides a swift path to completion, addresses all skill levels, has a supportive alumni network and boasts a high job success rate for graduates.

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.

You will be on your way to becoming an IT professional. Our Deep Diver graduates are earning $60k-$80k after just a couple of years. Our program has over a 90% graduation rate! 

Gain In-demand Skills Employers Need

Data Science Professionals are in demand everywhere. 

Here is just one of many student testimonials:
"The bootcamp was a life changing experience for me and jump started my career as a software engineer" Jack Reuter

Summer class offered.

Tuition Assistance Available

For questions or to discuss the tuition assistance options available, please contact Annalise Jaramillo at workforce@cnm.edu or 505-224-5206.   

https://cnmingenuity.org/funding-resources/

100% funding for any New Mexico resident with financial need.

Also, CNM Ingenuity is designated as a Workforce Innovation & Opportunity Act (WIOA) Eligible Training Provider (ETP) in the Central Region of New Mexico. This is an approved program, and WIOA funding is available to eligible individuals. Contact the New Mexico Workforce Connection WIOA Adult & Dislocated Worker Program at WIOA@wccnm.org or call 505.843.1900 for more details about tuition assistance, supportive services, and the eligibility and enrollment process.

1. Code a data science project in Python. 
2. Code a data science project in the R language. 
3. Download data from the web and API sources. 
4. Use data wrangling techniques to prepare and refine raw data sets. 
5. Access specific data fields in a database using SQL queries.  
6. Use existing data visualization tools to visualize data. 
7. Produce code for supervised learning and classification. 
8. Produce code for unsupervised learning and classification. 
9. Produce code for natural language processing. 
10. Produce code for artificial intelligence applications. 
11. Perform data science processing tasks in the cloud. 
12. Utilize Github as a code repository and as a code portfolio for employers.