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About this course

Data analysts and data scientists widely agree that most of their time is spent preparing and cleaning data for analysis. It may not be the most exciting part of the job, but it’s definitely an indispensable one.

In this course, we’ll teach you how to further leverage Python to supercharge your data analysis workflow. You’ll work in a real-world dataset to learn new concepts and techniques to enhance the speed and efficiency of your Python code. In this power-packed course, you’ll learn how to manipulate, combine, transform, and merge data, manipulate strings, and work with missing values in Python.

This course focuses on:

  • Introducing intermediate data preparation concepts and techniques in Python.
  • Building proficiency in aggregating, combining, transforming, and cleaning data.
  • Developing skill in manipulating strings and working with missing values in Python.

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How Our Data Cleaning and Analysis in Python Course Works

In data science, there’s no escaping data cleaning or analysis. Datasets are often a disorganized mess, and you’ll hardly ever receive data that’s exactly the way you need it. That’s why data cleaning is such a critical skill for data professionals, especially data analysts and data scientists. We’ve designed this course for intermediate Python users and it builds upon the essentials covered in our previous Python lessons.

If you’re here to level-up your data analysis skills, you’ve come to the right place. Here at Dataquest, we believe in learning by doing. You’ll never have to sit through boring “training” videos or ineffective “fill-in-the-blank” problems. With Dataquest, you’ll acquire, refine, and retain in-demand data science skills by solving real problems with real code.

Throughout these lessons, you’ll be digging into a real-world dataset from the UN Sustainable Development Solutions Network. You’ll implement your data cleaning and analysis skills to overcome obstacles and answer questions about the World’s Happiest Countries report.

One of the most significant benefits of learning with Dataquest is that we support you in building a strong and compelling data science portfolio. We know that one of the first and most important things hiring managers and employers look for in a candidate is a portfolio that demonstrates they have the skills for the job. That’s why this course (and most courses here at Dataquest) concludes with a portfolio project that will require you to synthesize everything you’ve learned and put it into practice.

We want to help you develop a portfolio that hiring managers can’t ignore.

Additionally, once you sign up with us, you’ll become a part of our thriving and supportive community of data students and professionals — you’ll never learn alone! And if you ever need extra help, our powerful and responsive support tools are just a click away.

Here’s a glance at our Data Cleaning and Analysis in Python course:

  • This course is the seventh in the Data Analyst in Python Career Path. It consists of the six lessons listed below, which cover in-depth programming concepts in Python.
  • You’ll write real code with dozens of practice problems so you can apply your skills.
  • At the end of each course, you’ll complete a guided project to reinforce your new knowledge and expand your portfolio.
  • When you complete this course, you’ll receive a certificate that you can share with your professional network.
  • Once you complete this course, you’ll be ready for more advanced Python courses.
  • Engage with our friendly community of data professionals, get feedback on your projects, and keep building your skills.

Who Is This Data Cleaning and Analysis in Python Course For?

This course was designed for intermediate Python users who already have a firm grasp of the basics of Python programming. Whether you’re just beginning your data science journey or you’re revisiting the basics, this course is for you!

We’ve designed this course to help as many people as possible:

  • Data analyst beginners looking for fundamental data analyst knowledge
  • Python users seeking a deeper understanding of the inner workings of Python
  • People who want a career as a data analyst or data scientist
  • People seeking remote work
  • Anyone who works with data in telecommunication, finance, education, and healthcare
  • Junior data scientists or data analysts who want to advance in their current positions
  • Anyone who wants to be able to capture, process, and interpret data
  • Students who want to develop a competitive portfolio
  • Experienced Python users who want to fill in the blanks and brush up on the basics

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