This course page was last updated on 19 August 2024. Some details may have changed since then. Please check the FutureLearn website or the FutureLearn page for current opportunities.

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Data Science Projects and Applications

Attendance

Online

Typ

Professional training, online courses

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Fees

Regular fees: 79 EUR

Data science allows organisations to understand and interpret swathes of data and gain insights that allow for smarter decision making, driven by data.

This two-week course provides an overview of the key concepts in data science, from understanding regression to using K-means clustering.

Discover new data analysis techniques through engaging data science projects

Whether you’re beginning a career in data science or want to understand your organisation’s data better, this course will strengthen your knowledge of data analysis tools and techniques.

You’ll complete practical projects that will demonstrate real-world applications of data science. This will allow you to assess different data science scenarios and choose the best approach, grounded in a broad knowledge of data analysis methodology.
Explore data visualisation tools and methods

You’ll delve into different types of data analysis and explore how to create effective data visualisation using MySQL. Using case studies as a starting point, you’ll discover step-by-step data visualisation processes, from gathering the data to displaying the output.

With this knowledge, you’ll be able to solve problem statements with data visualisation and be able to apply this knowledge to your own work.
Develop your data manipulation and interpretation skills

Having explored data analysis methods, you’ll then learn to evaluate and interpret this data in a meaningful way.

With a solid understanding of how to collect, review, and evaluate data, you’ll be able to explain your findings and the supporting methodology.

By the end of this course, you’ll understand applied data science methods and concepts. You’ll have gained insights into a variety of analytical approaches to data and be able to use these to interpret data effectively.

What topics will you cover?

This video course will help you to learn the important concepts and theories of applied data science that you need to know to store, manipulate, and visualize huge chunks of data.

The course starts with an introduction to applied data science and a tutorial on how to set up a Jupyter notebook. You’ll then go on to understand linear regression using Boston data. As you advance, you’ll discover data visualization techniques and explore time series and data evaluation. You’ll also get to grips with extended data analysis with the help of a temperature analysis activity. Toward the end, you’ll be introduced to k-means clustering and gain a solid understanding of decision trees.

When would you like to start?
Start straight away and join a global classroom of learners.

    Available now
    Join - €79

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?

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

Classify effective data science techniques
Explore relevant data science case studies

    Practice your learnings on your own projects

Who is the course for?

This course is designed for anyone interested in learning about data science, particularly those looking to begin a career in data science of analytics. It would also be suitable for those wanting to better understand their organisation’s data and how to use and interpret it effectively.

What software or tools do you need?
You’ll need to download and install the Anaconda software to your Windows, MacOS, or Linux system. We’ll show you how to do this on the course.

Who developed the course?
Packt

Founded in 2004 in Birmingham, UK, Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals.

 

More Information

Typ

Professional Training, Online Courses

Attendance

Online

Posted on: