What's Next

What is next at UMBC?

Undergraduate: If you are interested in following up this path to Data Science mastery, then based on your current level of education you can apply for a BS in Computer Science at UMBC. Check https://shadygrove.umd.edu/academics/degree-programs/bs-computer-science-data-science-and-cybersecurity-tracks-available 

Graduate: If you have finished four years of University education, you may go for a MPS in Data Science, or just a PBC (Post Baccalaureate Certificate) in Data Science. UMBC’s Master of Professional Studies (MPS) in Data Science program prepares students from a wide range of disciplinary backgrounds for careers in data science. In the core courses, students will get a fundamental understanding of data science through classes that highlight machine learning, data analysis and data management. The core courses will also introduce students to ethical and legal implications surrounding data science. Beyond the core courses, students will take three courses in domain-specific pathways developed in collaboration with academic departments across the university. Through these pathways, students will be able to utilize the skills and techniques they learned in the core courses within their field or area of expertise. Check https://professionalprograms.umbc.edu/data-science/masters-of-professional-studies-data-science/ for more details. 

Other Resources

You may ask, what can I do to keep learning? The best thing you can do is to stay immersed and stay connected with the community via email newsletters and/or meetup groups. Some are listed here. 

• There are many Meetup groups and this is just one of them that is close to us: Bethesda Data Science, https://www.meetup.com/bethesda-data-science-networking-meetup/ 

• UMBC Training Centers (Not part of UMBC, but founded by UMBC Alumni) offers some free online/on-premise seminars in addition to paid courses, https://www.umbctraining.com/ 6996 Columbia Gateway Drive, Suite 100, Columbia, Maryland 21046, USA, 443-692-6599

• Free online courses from Harvard University (via EdX), 

  • Data Science: Machine Learning (8-weeks long), https://pll.harvard.edu/course/data-science-machine-learning 

  • Machine Learning and AI with Python (6-weeks long), https://pll.harvard.edu/course/machine-learning-and-ai-python 

  • Etc. 

The following subscriptions are all FREE - do not pay!

• Daily Dose of Data Science, https://blog.dailydoseofds.com/ 

• Deeplearning AI, https://www.deeplearning.ai/ 

• Machine Learning Mastery, https://machinelearningmastery.com/ 

• Analytics Vidhya, https://www.analyticsvidhya.com/ 

• FourthBrain, https://fourthbrain.ai/

• Abacus AI, https://abacus.ai/  

• DataCamp, https://www.datacamp.com/ 

• DataScienceSalon (AI & Data Weekly), https://roundtable.datascience.salon/

• The Hugging Face, https://huggingface.co/ 

• Kaggle, https://www.kaggle.com/ 

• KDNuggets, https://www.kdnuggets.com/ 

• John Snow Labs, https://www.johnsnowlabs.com/ 

• TLDR AI, https://tldr.tech/ 

• AI by Hand (this one is a bit advanced as it tries to teach all major AI models, using calcuations done by hand to explain how each one works.) https://aibyhand.substack.com/ 

• Find me on Twitter and LinkedIn where I keep posting items of interest. 

• Join the "Laboratory for Healthcare Engineering" Discord server (ask for the link).

• I also maintain a Twitter list on "Data Science and AI" to which you can subscribe at https://x.com/i/lists/1229642047377805312 

• My library of (links to) free books on Data Science / Machine Learning, etc, https://docs.google.com/spreadsheets/d/1IyoiTA7PXFvA2-KH09rSmpTiwCTZm1rj714aQfQ7ias/edit?usp=sharing