Course Description:
Start your journey to becoming a Data Analyst or Data Scientist using Python – one of the most popular programming languages in the world. No prior coding experience is required; you’ll start from scratch and learn how to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher.Â
You’ll begin your data analyst training with interactive exercises and get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, Seaborn, and many more. You’ll learn why Python for data analysis is so popular and work with real-world datasets to grow your data manipulation and exploratory data analysis skills.Â
This course has 8 modules including a course orientation module. Each module ends with an exercise which helps to gauge your understanding as you progress through the course. The course ends with a final project in which you will be applying everything you have learnt in the course.
- Basic computer literacy including ability to create and manipulate files and install software.
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- This course is suitable for anyone who has a desire to learn and advance in their career. No prior coding knowledge is needed.
- Anyone who has interests in working with data and deriving insights from it.
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- Anyone working in marketing, finance, local government, accounting, operations, sales, manufacturing, healthcare, financial services, or any other industry or function that collects and uses data.
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- Someone who wants to learn skills that increase earning potential and have a rewarding career.
- Learn programming fundamentals and Python basics that get you codingfrom day one.
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- Learn the essentials of object-oriented programming.
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- Learn to troubleshoot Python code.
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- Apply Python skills to data visualization with Pandas, Seaborn and Matplotlib
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- Complete an end-to-end data analytics final project.
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- Get you prepared and ready to dive into special topics like data analysis, data science,machine learning, artificial intelligence, and web development.
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Data Analysis with Python Course Outline
The Data Analysis with Python course starts with a gentle introduction to Python as a programming language and its’ use cases. You will have a big picture of the Python ecosystem for data analysis and data science. You will be guided through setting up of your own Python environment which you will use throughout the course. You will learn how to use the Jupyter Notebook, a web-based interactive computing platform which you will use throughout the course to write Python programs.
The key to mastering Python programming language is understanding the different data types that exists, their attributes and methods. This module will get you ready for the rest of the course as you learn the different data types such as Number, String, List, Tuple, Set, Range and Dictionary.
In this module, you will get introduced to performing arithmetic operations and use some built-in functions in Python.
At the end of this module, you will be able to identify the data type of a Python object.
Boolean logic is the foundation of decision-making in Python programs. You will learn about different comparison operators, how to combine them with logical operators, and how to use the Boolean outcomes to control the flow of your Python program. You’ll learn to use the following statements and many more:
- if/else/elif Statements
- for loop
- while loop
- break, continue pass Statements
A Python function is a re-usable piece of code that can be called to perform a specific task. In this module, you will be introduced to the concept of object-oriented programming as you build your own Python functions and learn to keep your program organized. You will learn to use the different types of function arguments including Keyword, Default, Required, and Variable arguments. You will also learn very useful built-in functions such as lambda and map.
NumPy is an essential Python package for data analysis and data science. You’ll learn to use some of the most popular tools in NumPy by exploring data arrays in Python. You will learn how to create and reshape arrays; and explore different array methods such as obtaining the minimum, maximum, cumulative sum, mean and so on.
With this module, you’ll learn why Pandas is the world’s most popular Python library, used for everything from data manipulation to data analysis. You’ll explore how to manipulate DataFrames, as you extract, filter, and transform real-world datasets for analysis. You’ll start by mastering the pandas basics, including how to inspect DataFrames and perform some fundamental manipulations. You’ll also learn about aggregating DataFrames, before moving on to slicing and indexing.
You’ll wrap up the module by learning how to visualize the contents of your DataFrames, working with a real-world dataset.
Seaborn is a powerful Python library that makes it easy to create informative and attractive data visualizations. This course module introduces how you can use Seaborn to create a variety of plots, including scatter plots, count plots, bar plots, and box plots, and how you can customize your visualizations. By the end of this course, you’ll be able to use Seaborn in various situations to explore your data and effectively communicate the results of your data analysis to others. These skills are highly sought-after for data analysts, data scientists, and any other job that may involve creating data visualizations.Â
The capstone project allows you to apply the skills you have learned in this course. You will carry out an end-to-end analysis on real-world tasks using real-world tools and workflows.
Real-World Data Analysis in Action
Ready to see your potential? Watch our "Data Analysis with Python" students tackle real-world projects, turning data into actionable insights. Join us to learn, apply, and excel!
