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.
Kurssprache: English
Beginner, Junior, Programming
Kursinformationen
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.
Was Teilnehmende lernen werden
- 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
Für wen dieser Kurs gedacht ist
- High School and College Students
- Domain Experts
Lernmaterial
Für diesen Kurs einschreiben
Anforderungen für Leistungsnachweise
- Den Leistungsnachweis erhält, wer in der Summe aller benoteten Aufgaben mindestens 51% der Höchstpunktzahl erreicht hat.
- Die Teilnahmebestätigung erhält, wer auf mindestens 50% der Kursunterlagen zugegriffen hat.
Mehr Informationen finden Sie in den Richtlinien für Leistungsnachweise.
Dieser Kurs wird angeboten von
Mohamed has his Master's degree in the field of Communication Technology Engineering from the University of Ulm. He is now a Ph.D. candidate and part of the openHPI research team with a focus on auto-assessment of programming exercises in MOOCs. Mohamed is currently working on integrating Jupyter notebooks with openHPI to provide supportive learning environments. In his leisure time, Mohamed likes to go to the gym, watch football and travel the world.
Hendrik ist wissenschaftlicher Mitarbeiter im openHPI-Team mit dem Schwerpunkt auf videobasierte Lehre. Nach dem Wirtschaftsinformatikstudium hat es ihn erst in den Bankensektor gezogen, später in die Trainingsabteilung eines deutschen Maschinenbauers. Jenseits von Schneideprogrammen, Studiosetups und Trainingskonzepten ist er vor allem in der Boulderhalle zu finden.