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
- Duration4 weeks
- Weekly study4 hours
- Included in an ExpertTrackCourse 1 of 3
Data Analytics Using Python: Statistics and Analytics Fundamentals
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.
Syllabus
Week 1
Introduction
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
Statistics
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!
Prove you're job ready
Highlight the new, job-relevant skills you’ve gained and supplement existing qualifications with a hard-earned, industry-specific digital certificate – plus one for every course within your ExpertTrack.
- Learn the latest in your chosen industry or subject.
- Complete each course and pass assessments.
- Receive certificates validated by the educating organisation.
- Create a shareable certificate link for your CV and LinkedIn.
- Impress employers with learning outcomes you can add to your CV.
- Make your career dreams a reality.
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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?
FutureLearn
FutureLearn is jointly owned by The Open University and The SEEK Group and has been providing online courses for learners around the world over the last eight years.
In collaboration with
Endorsed by
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