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This course is part of the Data Analytics Using Python ExpertTrack


Data Analytics Using Python: Statistics and Analytics Fundamentals

Learn the fundamentals of statistics and data analysis using Python

Data Analytics Using Python: Statistics and Analytics Fundamentals
  • Duration4 weeks
  • Weekly study4 hours
  • 100% onlineTry this course for free
  • Included in an ExpertTrackCourse 1 of 3
  • Get full ExpertTrack access$39/month

Do you want to make your organisation’s data more valuable? The first step is organising and structuring it for analysis. Data analysts need to use databases and other technologies to efficiently collect, organise and manipulate this data.

This course will help you learn how to confidently use the Python programming language to analyse data and conduct data modelling.

Familiarise yourself with data analytics techniques

You’ll compare data analytics and advanced data analytics, and discuss the fundamentals of statistics and its application in data analytics.

You’ll learn a range of different techniques that will enable you to manipulate data in different ways, and adjust your approach to suit the subject, circumstances, and time you have available.

Learn new Python functions

You’ll also use Python to support data wrangling and ingestion, and learn advanced data analysis techniques including data mining and machine learning.

As you solidify your new knowledge by reviewing real-world examples and theories, you’ll develop critical employability skills and a foundational knowledge in Python to set yourself apart from other candidates when applying for jobs across a range of industries.

Boost your career with data analytics skills

This course will further any prior understanding you have of working with data and analytics, and you’ll be able to add Python skills to your CV.

Upon completion of the full ExpertTrack, you’ll have the knowledge and confidence you need to apply your skills in a real-world professional setting.


  • Week 1


    • Welcome to the course!

      Welcome to the course.

    • Introduction to Data Analytics

      The exponential growth of big data, supported by increasingly sophisticated algorithms and enhanced computing power, has brought about the ‘age of analytics’. We'll learn about common data sources and key concepts.

    • Introduction to Advanced Data Analytics

      Now let's go a step further and dive into what we mean by things like data mining, machine learning, pattern matching, knowledge extraction and the CRISP-DM process.

    • Wrap-up

      To complete the week, let’s recap the key points covered so far.

  • Week 2


    • Introduction

      Introduction to the week's concepts.

    • Fundamental Statistics I

      Analytics is grounded in statistics. We use descriptive statistics to calculate averages and compare data sets to understand what is happening. Let's get a jump start on the fundamentals of statistics.

    • Fundamental Statistics II

      Now it's time to go deeper with the fundamentals of statistics and how to leverage statistics within advanced analytics.

    • Statistics in action using Excel

      Next, we’ll cover the basics of spreadsheets so you can comfortably navigate these applications and apply basic functions for data analysis.

    • Wrap-up

      Let's wrap up what we covered this week and reflect on the learning so far.

  • Week 3

    Introduction to Python programming

    • Introduction

      Introduction to the week!

    • Python overview and development environment setup

      New to programming with Python? Learn the introduction to Python programming and set the foundations from the ground up.

    • Python language basics

      Learn the building blocks of Python by creating variables, identifying types of data, and exploring basic operators as well as control flows and loops. Either use a Python interpreter or a Jupyter notebook for this section.

    • Wrap-up

      Let's wrap up the concepts for the week and reflect on the learning so far.

  • Week 4

    Data structures, sequences and functions

    • Introduction

      Introduction to this week's concepts.

    • Python Data Structure, Sequences and Functions

      Now that you have installed the Python learning environment and learned some of the programming language basics, you are ready to learn some advanced concepts and additional features of the language.

    • Wrap-up

      Now it's time to reflect on your learning throughout the course, complete the final assessment, and look to what's next!

What will you achieve?

By the end of the course, you‘ll be able to...

  • Compare data analytics and advanced data analytics
  • Discuss fundamentals of statistics and its application in data analytics
  • Define loops, conditional logic, various data structures and collections in Python
  • Create and use functions in Python

Who is the course for?

This course is suitable for:

  • business analysts or junior data analysts looking to develop their advanced data analytics skills and programming capabilities to achieve career progression within data analytics
  • those with existing programming capabilities looking to start a career in data analytics
  • those lacking the programming capabilities to conduct more advanced data analysis and modelling

What software or tools do you need?

During the course we’ll be using Jupyter notebook. We recommend you use a computer to access these elements.

Who will you learn with?

I truly believe that leveraging the correct technologies in the appropriate way can take us towards a more sustainable economy. My focus is on converging M&E Engineering with Data Science/Analysis.

Who developed the course?


The social learning platform with hundreds of online courses from a quarter of the world’s top universities.

In collaboration with

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About this ExpertTrack

Develop the fundamental Python programming knowledge and skills required to complete advanced analytics.

Start learning today - free 7-day trial

After your free trial you can:

  • Pay $39 per month to keep learning online
  • Have complete control over your subscription; you can cancel any time
  • Work at your own pace and set your own deadlines at every stage
  • Only pay while you’re learning; the subscription will cancel automatically when you finish
  • Complete online assessments to test your knowledge and prove your skills
  • Earn digital course certificates and a final award that you can share online, with potential employers, and your professional network
  • Keep access to the content of courses you complete even after your subscription ends