The ultimate goal of the bootcamp is to cultivate strong data science skills with an emphasis on machine learning techniques to satisfactorily meet and exceed the requests of the Data science world. In the process, we will develop good habits for operating independently as data scientists and for operating as members of productive data science teams.
Why is the topic relevant? Why is it on everyone's mind?
Having data science and machine learning skills nowadays can potentially increase your success chances, whether that be as an individual or a business. Many industries offer their employees the opportunity to enroll in upskilling programs. In that way, domain experts can leverage the knowledge in their given field and seek higher roles in their company. As the demand for data science skills rises higher and higher, having a rounded understanding of data science and applying that knowledge practically can help widen your scope of knowledge.
Who should take this course?
- People with basic python knowledge. That includes variables, conditional statements, while loops, and data structures.
- People with domain knowledge that need to apply modern data analysis in their daily workload.
What will be taught in the course?
- What is data science? why is it relevant?
- Data Analysis and making sense of the data you have.
- The use of libraries such as NumPy, Pandas, and Matplotlib for interesting data visualizations
- Leveraging the power of ML
How will it be taught?
- Videos
- h5p
- Quizzes
- Two live streams
What needs to be accomplished?
- Jupyter notebook Exercises
- Weekly challenges
- Exposure to real-life scenarios and datasets (no easy data)
How much time is expected to be spent?
The workload for the course is approximately 5 - 7 hours per week, depending on prior knowledge.
What you'll learn
- What is Jupyter Notebooks and how to use it for Data Science
- Work with real-life datasets and apply Numpy, Pandas and Matplotlib
- Use scikit-learn to create powerful ML models
Who this course is for
High School and College Students
Domain Experts
