This course is part of the Data Analytics Using Python ExpertTrack
Data Analytics Using Python: Data Wrangling and Ingestion
Enhance your understanding of Python by diving deeper into functions including data wrangling, manipulation and transformation.
- Duration4 weeks
- Weekly study4 hours
- Included in an ExpertTrackCourse 3 of 3
Data Analytics Using Python: Data Wrangling and Ingestion
Do you want to expand your data analytics skills and streamline your analysis processes? Having a solid understanding of Python can help to boost your career and make data analysis and manipulation considerably more efficient.
This course builds on the previous two within this Data Analytics Using Python ExpertTrack to give you a better understanding of the possibilities of using Python.
Deepen your understanding of Python functions
On this course, you’ll familiarise yourself with the data wrangling, manipulation and exploration steps of the CRISP-DM methodology, and perform data ingestion using Python.
You’ll learn how to demonstrate transformation activities in Python to further your data analysis.
You’ll also explore SQL in relation to data analytics, including the fundamentals of databases using SQL to perform various data analysis operations.
By the end of this course, you’ll be better equipped to create database tables using the data definition language and add data records using data manipulation language.
You’ll have also practised how to query the data stored in those database tables, and demonstrate various data processing activities using data query language and data manipulation language.
Syllabus
Week 1
Data wrangling using Python I
Introduction
Introduction to the week
What is data wrangling?
What is data wrangling and why does it matter?
Data wrangling using Python
How do we wrangle data using Python? Let's find out.
Wrap-up
Wrap up of this week's concepts.
Week 2
Data wrangling using Python II
Introduction
Introduction to the week
Data wrangling using Python II
Let's look at some intermediate approaches to wrangling data using Python.
Wrap-up
Wrap up of Week 2's concepts.
Week 3
Designing databases
Introduction
Introduction to the week.
Designing databases
Let's look at the fundamentals of designing databases.
Wrap-up
Wrap up of this week's concepts.
Week 4
Introduction to SQL
Introduction
Introduction to the week
Introduction to SQL
Let's look at the fundamentals of using SQL to perform analysis.
SQL for data analysis
How do we use SQL to analyse data? Let's find out.
Wrap-up
Now it's time to wrap up this week's concepts, look to what the future holds and demonstrate your learning in the final test.
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What will you achieve?
By the end of the course, you‘ll be able to...
- Demonstrate data wrangling, manipulation and transformation activities in Python
- Create database tables using the data definition language and add data records using data manipulation language
- Query the data stored in those database tables
- Demonstrate various data processing activities using data query language and data manipulation language
Who is the course for?
This course is suitable for:
- business analysis or junior data analysts looking to develop advanced data analytics skills and programming capabilities to progress their careers in data analytics
- someone with existing programming capabilities looking to enter the data analytics field
- an individual lacking the programming capabilities to conduct more advanced data analysis and modelling
What software or tools do you need?
During the ExpertTrack 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.
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Endorsed by
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