Data Analysis and Machine Learning
| Code | Completion | Credits (ECTS) | Range | Language |
|---|---|---|---|---|
| 126YASU_K | Z | 2 | 8B | Czech |
- Course guarantor:
- Karel Klouda
- Lecturer:
- Tutor:
- Karel Klouda, Václav Nežerka
- Supervisor:
- Department of Construction Management and Economics
- Synopsis:
-
In this course, students will be introduced to modern methods of data analysis and machine learning. We will begin with the basic Python tools for working with data, from data loading and cleaning to visualization. We will then explore fundamental statistical methods for data analysis and gradually move on to more advanced machine learning techniques.
Students will learn how to properly evaluate and validate their models, analyze time series, and explore data using cluster analysis. Towards the end of the course, we will introduce state-of-the-art deep learning techniques and neural networks.
Overall, students will acquire the skills needed to become effective data analysts capable of applying their knowledge to a wide range of real-world problems.
- Requirements:
- Syllabus of lectures:
-
1. Introduction to Data Analysis
2. Fundamentals of Data Structures and Data Manipulation in Python
34. Data Exploration, Visualization, Cleaning, and Preprocessing
3. Basic Statistical Data Analysis
4. Introduction to Machine Learning
5. Decision Trees
6. Linear Regression
7. Model Evaluation
8. Time Series Analysis
9.. Cluster Analysis
1213. Neural Networks
- Syllabus of tutorials:
- Study Objective:
- Study materials:
-
1) Peng, R., Matsui, E. The Art of Data Science. Lulu.com, 2016. ISBN: 978-1365061462
2) Géron, A. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition. O'Reilly Media, Inc, 2019. ISBN: 978-1492032649
3) Goodfellow, I., Bengio, Y. and Courville, A. Deep Learning: MIT Press, 2016. ISBN: 978-0262035613
- Note:
- Further information:
- https://moodle-ostatni.cvut.cz/course/view.php?id=541
- Time-table for winter semester 2026/2027:
-
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Wed Thu Fri Sat - Time-table for summer semester 2026/2027:
- Time-table is not available yet
- The course is a part of the following study plans:
-
- Digitalizace ve stavebnictví - kombinovaná forma studia (compulsory elective course)