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About

About Data Driven World (DDW)

This course provides fundamentals for students with the necessary skills in a data driven world. The first half of the course focuses on providing students with algorithmic thinking and different paradigms of computation such as procedural, object-oriented design and state machine. The second half of the course focuses on a basic introduction to machine learning for categorical and continuous data. Students will be able to apply both algorithms and basic machine learning techniques to solve real-world problems driven by data and computation.

Prerequisite

10.014 Computational Thinking for Design (Term 1)

Learning Objectives

By the end, students should be able to:

  • Analyse different algorithms’s complexity in terms of computation time using Python computational model
  • Identify recursive structure in a problem and implement its solution in Python
  • Explain UML diagrams and design software using basic UML diagrams
  • Apply appropriate data structure and implement them using object oriented design
  • Implement algorithm to find coefficients for linear regression by minimizing its error
  • Implement algorithm to classify categorical data using logistic regression for binary category and above
  • Analyse and evaluate linear regression using mean square error and correlation coefficient
  • Analyse and evaluate logistic regression using confusion matrix, its accuracy and recall
  • Design state machine and implement it using object oriented paradigm
  • Fix syntax errors and debug semantic errors using print statements

Text References

Instructors will provide reading materials for each week. The references for this course include:

Instructional Methods and Expectations

The course will be run using a project-based and flipped-classroom strategy. Students are expected to do pre-class activities before coming to class. In-class hours are used to discuss and solve problems as well as to do projects. Each week there are mini-projects related to the topics just introduced in that week and it culminates in one open project at the end.

Students are expected to do their pre-reading and homework on their own while discussing the cohort sessions and projects with the instructors in class. There will be hands-on programming activities for all cohort sessions.

Lesson Format

Each week we allocate 5 hours of cohort lessons. You are recommended to spend 1.5 hours for pre-class activities and 5.5 hours for homework and mini projects weekly as well.