Course Overview
The course introduces students to programming in Python, programming environments, and cloud computing tools for solving engineering, design, and research problems. Students learn version control (git), environment setup and management, and use of tools such as Jupyter Notebook, VS Code, PyCharm, and Google Colab. Core programming concepts include data types, control structures, object-oriented programming, and key Python libraries (NumPy, Pandas, Matplotlib, SciPy, SymPy, Scikit-learn). The course emphasizes exploratory data analysis, numerical methods, symbolic computation, and introductory machine learning, with practical tasks implemented in Python and cloud-based environments.
MAIN GOAL
To equip students with knowledge and practical skills in Python programming, computational tools, and cloud technologies for solving analytical, design, and research problems in engineering.
Learning Outcomes
On completion of this module the learner will gain:
- + Proficiency in Python programming and use of programming environments.
- + Competence in exploratory data analysis and visualization.
- + Skills in numerical and symbolic computations using Python libraries.
MEET YOUR INSTRUCTORS
Course Co-ordinator
Admissions
Entry Requirements
- + Basic knowledge of mathematics and physics.
Teaching and Assessment Methods
- + Lectures: 15h
- + Laboratories: 45h
- + Project: 15h
- + Assessment: Based on project (50%) and two programming tests (50%).
Application Deadline: Check institution page using link below
Fees & Funding
Tuition Fees
Visit institution page for information on fees and application deadlines.
Click here to visit institution page
Practical Notes
Contact Patryk Jasik for any additional information relating to this course.
