Chanukya Patnaik Chanukya is the founder of DPhi - Data Science community with a mission to educate and build AI for everyone.

Data Science Bootcamp in Korea – an initiative by DPhi – Call for Volunteers

1 min read

About DPhi:

DPhi is a Global Data Science community that started with a vision to build data culture and democratize Data Science learning. The community currently comprises of passionate Data Scientists and Data Science Enthusiasts who enjoy learning, sharing knowledge, and love giving back to the community.

About the initiative:

Data Science Bootcamp in Korea is an initiative aimed at providing Data Science Education in the native language of Korea with the help of the experts in the community. We believe the contributions made by several Data Scientists to this initiative will go a long way in educating many budding Data Science/AI enthusiasts in Korea. It doesn’t just stop with education, but it will go a long way in shaping the future of A.I in the nation.

Language of instruction: Korean

Topics for which we need speakers: We already have 3 speakers, we are looking for speakers for the rest of the sessions.

  1. Introduction to Data Science – its prominence and use-cases
  2. Python Basics for Data Science & Hands-on session on Pandas
  3. Data Visualization & Hands-on session using Matplotlib
  4. Introduction to Descriptive Statistics & Exploratory Data Analysis
  5. Fundamentals of Data Pre-processing
  6. Introduction to Machine Learning (covers end-end pipeline intuitively) & building your first Machine Learning Model using Decision Tree
  7. Introduction to Regression Problems & hands-on problem-solving using Linear Regression
  8. Introduction to Classification Problems & hands-on problem-solving using Logistic Regression (confirmed)
  9. Fundamentals of Machine Learning Model Evaluation Metrics, Cross-Validation & Hyperparameter tuning
  10. Ensembling models and hyperparameter tuning
  11. Session on Feature importance and feature selection (Recursive Feature Elimination (RFE), Feature Importance using Random Forest, Boruta, XGBoost)
  12. Applied Problem Solving (2 Sessions on how to solve problems)

The exhaustive curriculum for 5 weeks can be found here.

The learning path will be similar to this.

Teaching Pedagogy that worked for us:

  • Make learners understand intuition first. Once they understand something intuitively it is easy for them to understand the mathematics and statistics behind it. So for live sessions, we purely make it a practice to just teach intuition.
  • Explain what, why, and how to do it?
  • “How to do it?” in the above point refers to hands-on sessions. Learners get what they see, that’s the best part of a hands-on session where the tutor runs the code live and shows them the output. It also keeps the learners captivating throughout the session
  • Our Educators Guidelines can be found here.

Format of the Bootcamp:

  • Day-wise modules: We will publish day-wise learning modules/challenges that include self-paced learning material of concepts, jupyter notebooks, quizzes, assignments
  • Live sessions: There will be 2-3 live classes every week by Data Science experts
  • For real-time communication, we will be using Slack. This medium will help learners to clear doubts on a real-time basis if they are stuck somewhere. In addition, this will also allow learners to interact with the mentors and fellow learners
  • Certification: At the end of the Bootcamp we will provide a certificate based on the performance of the learners

You may also want to go through this Bootcamp of ours which covers most of the FAQ’s:

If you are interested to contribute or know someone who wants to contribute to this initiative, please write to us at [email protected]


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