Introduction to Python and Data Analysis - 4 days Online Classroom
2.650,00 EUR
- 4 days
Build a strong foundation in Python programming and data analysis with this practical, hands-on course. Introduction to Python and Data Analysis equips you with the essential skills to work with data using Python’s most popular libraries and tools. Through real-world examples and guided exercises, you’ll develop the confidence to use Python for everyday data tasks, reporting, and decision-making support in business and technical environments.
Key Features
Language
Course material in English
Level
Beginner level
4 days (8 hours/day) online instructor-led
50+ recommended study hours
Hands-on coding practice throughout the course
Use of live lab environments with guided feedback
Industry experts delivering real-world insights
Comprehensive course content and example data sets
Ask for date confirmation!
Program completion certification included
Learning Outcomes
At the end of this program, you will be able to:
Getting Started with Python
Learn Python basics using interactive and script-based methods, focusing on clean syntax, code structure, and readability.
Working with DataFrames
Use Pandas DataFrames to load, clean, transform, and manage datasets, including handling missing data and modifying structures.
Grouping and Aggregating Data
Apply the split-apply-combine approach in Pandas to group data and generate meaningful summaries and insights
Data Visualisation with Matplotlib
Create charts and plots such as bar charts, histograms, and line graphs to clearly communicate data insights.
Course timeline
Day 1
Session 1: Introduction
- Python basics and execution modes
- Statements, comments, and indentation rules
Session 2: Variables & Scalar Types
- Numbers, text, and booleans
- Variables and type() function
Session 3: Operators & Expressions
- Arithmetic, comparison, and logical operators
- Assignment and membership operators
Session 4: Containers
- Lists, tuples, sets, and dictionaries
Day 2
Session 5: Conditions & Loops
- If/else statements
- For and while loops
- range() function and iteration
- break and continue
Session 6: Functions
- Built-in functions (len, sum, min, max, sorted)
- Defining functions
- Positional, named, and default arguments
Session 7: Objects
- Introduction to classes
- Attributes and methods
- Working with built-in container methods
Day 3
Session 8: Introduction to DataFrames
- Understanding DataFrames and key attributes
- Loading, writing, and exploring data
- Subsetting and conditional filtering
- Adding/removing columns
- Aggregations and handling missing values
Day 4
Session 9: Groupby and Aggregation (Split-Apply-Combine)
- Grouping data by one or more columns
- Applying single or multiple aggregation functions
- Generating summarized insights from datasets
Session 10: Plotting with Matplotlib
- Creating bar charts, histograms, and line plots
- Visualising data patterns and trends
- Presenting analysis results clearly and effectively
Who Should Enroll in this Program?
Beginners in Python programming
Aspiring data analysts
Business analysts working with data
IT professionals transitioning into data roles
Prerequisites
- Basic computer literacy
- No prior Python experience required
- Familiarity with spreadsheets (e.g., Excel) is helpful but not essential
- Basic understanding of data concepts is beneficial
Statements
Licensing and accreditation
The course is offered according to Partner Program Agreement and complies with the License Agreement requirements.
Equity Policy
Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.
Frequently Asked Question
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