Course Content
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Introduction to Data Analysis
- What is data analysis
- Why data analysis
- Types of data analysis
- Process flow of data analysis
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Introduction to NumPy
- Pandas & NumPy Intro
- Numpy Arrays & Array Properties
- Array Creation
- Random Number Generation
- Indexing & Slicing Arrays
- Array Operations
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Introduction to Pandas
- Defining pandas library
- Why do we need pandas library
- Pandas data structure
- Exploring the data of a DataFrame
- Selecting data from DataFrame
- Data cleaning in pandas DataFrame
- Grouping and aggregation
- Sorting and ranking
- Adding row into DataFrame
- Adding column into DataFrame
- Dropping the row/column from DataFrame
- Concatenating the dataframe
- Merging/joining the dataframe
- The merge() function
- The join() function
- Writing the DataFrame to external files.
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Data Visualisation with Matplotlib
- What is data visualisation
- What is Matplotlib
- Getting started with Matplotlib
- Line plot using Matplotlib
- Customising the plot
- Some basic types of plots in matplotlib
- Export the plot into a file
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Working with Real-World Data (APIs & JSON)
- Introduction to APIs
- Understanding JSON Data
- Making API Requests in Python
- Working with API Data
- Converting API Data to DataFrame
- Data Analysis with API Data
- Automating Data Collection
- Business Applications
Course Dates, Prices & Enrolment
Scroll right for more details
| Delivery Method | Dates & Times | Hours | Price | Enrolment |
Online Training using Zoom
|
08 Jun 2026 - 12 Jun 2026
Mon, Wed & Fri
10:00 AM - 02:00 PM
BT
| 12-hour over 3-day |
| Enrol Now |
Online Training using Zoom
|
22 Jun 2026 - 03 Jul 2026
Mon, Wed & Fri (2 wks)
03:00 PM - 05:00 PM
BT
| 12-hour over 6-day |
| Enrol Now |
Online Training using Zoom
|
04 Jul 2026 - 18 Jul 2026
3 Saturdays
03:00 PM - 07:00 PM
BT
| 12-hour over 3-day |
| Enrol Now |
Online Training using Zoom
|
16 Jul 2026 - 17 Jul 2026
Thursday to Friday
10:00 AM - 04:00 PM
BT
| 12-hour over 2-day |
| Enrol Now |
Online Training using Zoom
|
20 Jul 2026 - 31 Jul 2026
Mon, Wed & Fri (2 wks)
03:00 PM - 05:00 PM
BT
| 12-hour over 6-day |
| Enrol Now |
Online Training using Zoom
|
10 Aug 2026 - 14 Aug 2026
Mon, Wed & Fri
10:00 AM - 02:00 PM
BT
| 12-hour over 3-day |
| Enrol Now |
Online Training using Zoom
|
05 Sep 2026 - 19 Sep 2026
3 Saturdays
03:00 PM - 07:00 PM
BT
| 12-hour over 3-day |
| Enrol Now |
Online Training using Zoom
|
17 Sep 2026 - 18 Sep 2026
Thursday to Friday
10:00 AM - 04:00 PM
BT
| 12-hour over 2-day |
| Enrol Now |
Note: Online classes are usually delivered through Zoom video conferencing.
Price Calculator & Booking Request Form
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Frequently Asked Questions
Do I need prior Python knowledge for this course?
Basic knowledge of Python is recommended for this course. You should be familiar with fundamental concepts such as variables, data types, loops, and functions. If you are new to Python, we recommend completing a beginner-level Python course first.
What will I learn in this course?
You will learn how to analyse data using Python, including working with libraries such as Pandas and NumPy. The course covers data cleaning, manipulation, analysis, and basic visualisation techniques to help you extract insights from real datasets.
Will I get hands-on experience during the course?
Yes, this course is highly practical and includes hands-on exercises and real-world examples. You will work with datasets to apply your knowledge and build confidence in data analysis.
What tools or software will I use?
You can use a range of tools to work with Python during this course. We typically recommend using Jupyter Notebook (via Anaconda) or Google Colab, as they are widely used for data analysis.
You can also use other development environments such as Visual Studio Code, PyCharm, or Spyder, as long as you have the required libraries installed, including Pandas, NumPy, and Matplotlib.
If you prefer not to install anything, you can use our browser-based platform, which includes all the required libraries:
py.lait.co.
If needed, we will guide you through the setup process before the session.
Is data analysis with Python useful for my career?
Yes, data analysis with Python is a highly in-demand skill used in roles such as Data Analyst, Data Scientist, and Business Analyst. It allows you to work with large datasets, automate analysis, and generate insights for decision-making.
What jobs can I apply for after completing this course?
After completing this course, you can pursue roles such as Data Analyst, Junior Data Analyst, Reporting Analyst, or Business Analyst. It also provides a strong foundation for advanced roles in data science.
Is this course enough to become a data analyst?
This course provides essential data analysis skills using Python. To become a well-rounded data analyst, it is recommended to combine this with other skills such as SQL and Power BI for data querying and visualisation.
How is the course delivered?
The course is instructor-led and can be attended live online, in person at our London training centre, or delivered on-site at your organisation for corporate training.
Will I receive a certificate after completing the course?
Yes, you will receive a certificate of completion after successfully finishing the course.
What should I learn after completing this course?
After completing this course, you can progress to advanced data analytics topics, machine learning, or combine your skills with SQL and Power BI to build a complete data analytics skill set.