Course Description
Unlock the power of data analysis with Python in this immersive crash course designed for beginners and intermediates alike. This course will guide you through the fundamental tools, libraries, and techniques required to analyze, manipulate, and visualize data efficiently. You’ll dive into hands-on coding exercises, real-world datasets, and practical projects to build confidence in your ability to tackle data-driven challenges. By the end, you’ll not only be proficient in Python programming for data analysis but also equipped to apply these skills in diverse fields like business, research, and technology. Whether you’re just starting or brushing up on your skills, this course is your fast track to becoming a Python data enthusiast.
Learning Objectives
The key learning objectives for this course are the following:
Understand the fundamentals of Python programming and its applications in data analysis. Learners will gain a solid grasp of Python basics, including its syntax, variables, and data types, while understanding how Python serves as a powerful tool for data analysis.
Gain proficiency in essential Python libraries like NumPy, Pandas, and Matplotlib/Seaborn. This course introduces learners to popular Python libraries used for data analysis, enabling them to perform computations, manipulate datasets, and create data visualizations with ease.
Learn to clean, preprocess, and manipulate datasets for analysis. Participants will master techniques to handle missing data, reshape datasets, and prepare raw data for analysis, ensuring it's accurate and ready for further exploration.
Develop skills to explore data, identify patterns, and extract insights using Python. Learners will practice analyzing datasets to uncover trends, anomalies, and correlations that can inform decision-making.
Create compelling data visualizations to present findings effectively. Through Matplotlib and Seaborn, learners will design visually engaging and insightful graphs, charts, and plots to communicate complex data-driven stories.
Work with real-world datasets to solve practical data analysis problems. By tackling real-world datasets, learners will gain hands-on experience in applying analytical techniques to problems that mirror industry scenarios.
Build a solid foundation for advanced topics such as machine learning or big data. This course sets the stage for further exploration of advanced topics, equipping learners with the foundational skills needed to progress to specialised fields like machine learning or big data analysis.
Course Schedule
Lesson 1: Introduction to Python for Data Analysis
1h 30min | 17 February 2025 | 18:00 - 19:30 (CET)
This lesson introduces learners to Python programming essentials, including its syntax, data types, and variables. Also get a strong foundation in Python’s core data structures - such as lists, dictionaries, tuples and sets - and explore how to control the flow of their programs with loops and conditionals. Learners will also get hands-on experience with Jupyter Notebook, an interactive coding environment widely used for data analysis. By the end of this session, participants will have written their first Python program and feel confident navigating the programming environment.
Lesson 2: Working with Libraries: NumPy
1h 30min | 18 February 2025 | 18:00 - 19:30 (CET)
This lesson introduces NumPy, a powerful library for numerical computations and array manipulations. Participants will learn to create and manipulate arrays, perform mathematical operations, and use broadcasting to handle data more effectively. These skills are vital for managing numerical datasets in future lessons.
Lesson 3: Data Wrangling with Pandas
1h 30min | 19 February 2025 | 18:00 - 19:30 (CET)
Pandas, a cornerstone library for data manipulation, is the focus of this lesson. Learners will work with DataFrames and Series, clean messy datasets, handle missing values, and transform data into a structured format ready for analysis. By the end of the lesson, participants will have mastered the tools needed to reshape and refine datasets.
Lesson 4: Data Exploration and Visualisation
1h 30min | 20 February 2025 | 18:00 - 19:30 (CET)
In this session, participants will explore datasets using descriptive statistics, grouping, and aggregating methods. They will learn how to sort, filter, and summarize data to identify trends, outliers, and meaningful patterns, laying the groundwork for extracting actionable insights from raw information. This lesson will also focus on creating visually engaging and informative charts using Matplotlib and Seaborn. Learners will design line, bar, and scatter plots while customizing visual elements like labels, colors, and styles. These skills will help participants communicate data insights effectively.
Lesson 5: Working with Real-World Data & Final Project
1h 30min | 21 February 2025 | 18:00 - 19:30 (CET)
Participants will apply their knowledge to analyze real-world datasets, tackling practical challenges like cleaning, exploring, and visualizing data. The lesson emphasizes combining libraries like Pandas, NumPy, and Matplotlib to generate comprehensive insights. Participants will define a problem, clean and explore the data, perform analysis, and create visualizations to present their findings. This project reinforces their skills and provides a tangible portfolio piece to showcase their expertise.
Course Instructor

Humzaa Imtiaz Ullah
Chemical Engineer
The course is offered by Humzaa Imtiaz Ullah. He is a graduate of BSc and MSc in Chemical Engineering from the Technical University of Denmark, where he gathered a strong foundation within Python, MATLAB and R with focus on Data Analysis. He has a strong experience from working in the industry within Pharmaceutical, Cement, Education and Consulting. He has continuously applied his coding and programming skills within his workplace, with main focus on analysing large sets of data allowing the organisation to make data-driven decision.
Any Questions?
Are you unsure whether this couse covers what you are looking for? Or you have any other question? Then feel free to get in touch with our team at info@chemengglife.com and we will be more than happy to assist in anyway we can! :)