This course aims to provide students with a strong foundation in programming and problem-solving for data-centric tasks. It equips learners with the ability to design, implement, and evaluate basic programs, apply logical and algorithmic thinking, and utilize essential tools for data manipulation and analysis. By the end of the course, students will be prepared to approach data-driven problems with structured solutions and fundamental computational skills.

This course introduces students to the fundamentals of programming and problem-solving for data-driven tasks. It begins with an overview of programming concepts, computer systems, number systems, and algorithmic logic, followed by core Python topics such as variables, data types, operators, expressions, conditional statements, loops, and functions. Students then learn to work with data structures including lists, tuples, dictionaries, and sets, as well as file handling techniques. The course also covers the use of essential data science libraries for basic data analysis and visualization and emphasizes algorithmic problem-solving skills. The semester concludes with a project presentation where students apply their programming and analytical knowledge to a practical data-related task.

Theoretical lectures, laboratory applications, exams, discussion, question-answer, homework, project, individual study.

Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud 1st Edition, Pearson (September 17, 2021) by Paul Deitel, Harvey Deitel.