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.
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.
We organized the course in six weeks and two tracks:
The CORE track
- Week 1 of the course is all about the „Why“. It outlines data science, its relevance, and its potential.
- Week 2 is about the „How“. Different approaches to analyzing your data to find meaningful relations and perform a well-rounded EDA.
- Week 3 dives into various Machine Learning algorithms and techniques that are essential in any data science project.
- Week 4 is the final exam week. After week 4, the core track ends.
The PROJECT track
- Week 5 & 6 is where the real experience starts and you are invited to continue with two extra weeks to work on a real-life challenge with dedicated tools.
We encourage you to sign up and enroll for the total six week experience to foster a solid understanding and apply your new skills!
Here's a tentative timeline, deadlines, and other dates might still be subject to change.
The workload for the course is approximately 5 - 7 hours per week, depending on prior knowledge. It is hard to give a distinct number, given that some topic might be easier for your or spark an unknown desire to learn more, this number could be higher. As we are aware that this course is done "next" to an existing work, study or other load, we balance your time resources accordingly.
We are looking forward to see you in the course!
Find out more in the certificate guidelines.
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 is part of the openHPI research team with a focus on videobased learning. After earning his degree in the field of information systems, he worked in the banking and technology sector. Beyond of cutting software, studio-setups and designing curricula, he can be found in the local climbing gym.