

General Assembly's Data Science Short Course empowers learners to create predictive models using statistics and Python. Delivered both in-person and online, this course builds confidence in tackling machine learning challenges. Participants engage in hands-on activities within a virtual classroom setting, enhancing their practical skills and professional credibility.
Ideal for aspiring data scientists and analysts
Open to technical and non-technical backgrounds
No prerequisites required
In-person and online virtual classroom options
Hands-on activities with Python and statistics
Expert-led instruction on predictive modeling
Develop predictive modeling skills
Gain practical experience with Python
Enhance career opportunities in machine learning
No certifications are covered by this course.
Graduate 2021
This course was really great to learn about the different applications of leveraging python for data science. I really enjoyed the two part presentation (apply learning to a dataset of your choice - presenting your analysis at two points during the course.)Definitely gave me confidence to continuing learning in this field.Overall, course is great for anyone currently doing some degree of analytical work and who would like to expand their skill set.
Graduate 2019
The part-time data science course was a fantastic crash course in data science with Python. Ben did an amazing job taking us through all of the different parts of the machine learning process (after reviewing the Python basics to get us ready to work through all of it), and we then were able to get the practical experience of putting together our own projects and presenting them in front of the class, which was invaluable. The course was structured very well, as each bit of information built on top of the last. I would happily recommend this course to anyone who wants to learn data science and can't commit to a boot camp!
Student 2018
An incredible (and practical) introduction to data science. I wish college courses were like this. It was so much information. Since we applied everything we learned I got a lot out of this class and can do a lot more than I expected I would with only 60 hours of class time. For me, pre work and homework too about double the estimated time but it was definitely worth the effort. Those with prior experience in either statistics or programming will have a leg up, but it's not necessary to get started.
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