Data Visualisation with Python

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Learn Path Description

Develop data visualization skills leveraging Python. Do you want to boost your data visualization and Python skills to transform data into meaningful insights that add real business value? As data analysis becomes an increasingly essential practice across industries like finance, marketing, healthcare, and education, the demand for data analytics skills is rising dramatically. Leverage Python libraries to conduct data modelling On this ExpertTrack, you’ll learn to leverage Python libraries to conduct data modelling and create compelling data visualizations. You’ll master key Python functions such as Matplotlib to create plot bar charts, histograms and scatter plots. You’ll also learn how to use Seaborn, another data-visualization library, to combine aesthetic appeal and powerful technical insight, as well as Bokeh, to create complex interactive visualizations using advanced layout widgets. Interpret and analyze data sets As you progress through the courses, you’ll learn how to interpret quantitative comparisons and statistical visualizations, and identify different types of data plots. You’ll examine uncertainty in data, point estimate intervals, and confidence bands so that you can learn how to display uncertainty in data and walk through creating a workflow of a visualization based on exploring a dataset. Communicate data insights to stakeholders Many organizations collect and analyze data effectively but are unable to transform their insights into effective decision-making that results in organizational value. Throughout this ExpertTrack, you’ll develop advanced data visualization skills that will help you bring insights to life and convey data in an accessible and meaningful way. The courses will guide you through a number of practical exercises, asking you to design powerful visualizations of your own using spreadsheet tools. You’ll conclude your training by considering data analytics as an emerging field, and exploring the role of new technologies and practices such as UX design and DataOps. Once you’ve completed all 3 courses, you’ll feel confident in applying design thinking, creating dashboards, leveraging a variety of data visualization tools, and applying data insights. Are data visualization skills in demand? Yes. Job postings calling for data visualization have grown by 540% over the last five years and specific demands for Tableau skills have grown by 1,165%. Individuals that can combine foundational skills such as data wrangling and statistical analysis, with the use of Python can quickly gain traction in this growing field as a business or data analyst. Industry statistics Median base salary£45,000UK job openings/month 1,724Source: Glassdoor's Best Jobs (2020)

Skills You Will Gain

Courses In This Learning Path

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Total Duration

4 weeks

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Level

Beginner

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Learn Type

Certifications

Data Visualisation with Python: Matplotlib and Visual Analysis

While many organisations are capable of collecting and analysing data efficiently, not all can transform these insights into organisational value. Data visualisation is a great tool. The Python online course will help you improve your data visualization skills, both for exploratory and explicatory purposes. It uses the most common programming language. Python is widely used in all areas of business analytics, including finance and healthcare. It is also one of easiest programming languages to learn. Through the use of Python's robust graphic libraries, you will learn to use it to bring your ideas to life and create stories that aid decision-making. This course will teach you design basics, helping you identify and critique the components of visualised data, charts, and complex relationships. In this course, you will also learn how to create powerful visualisations with spreadsheet tools. Matplotlib, a Python library that creates charts and plots, is powerful. The library and time series data will be explained to you, which is one of the most common data types. Additionally, you will learn how to create and customize plots with Python code. This includes custom colours, markers, styles, and other options. Visualisations are a way to visualize data and compare them in a quantitative fashion. We'll show you how to create quantitative visualisations using different methods. Learn how to plot scatter plots, histograms, and bar charts using Matplotlib, Python plotting library, Matplotlib. You can preview some of the steps in this course before you sign up.

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Total Duration

4 weeks

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Level

Advanced

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Learn Type

Certifications

Data Visualisation with Python: Seaborn and Scatter Plots

This course will show you how to visualize big data using Python programming language. This course will introduce you to Python for beginners in data analysis. Python is one the most popular and easy-to-use programming languages. It powers the back-ends for some of the largest online companies like Google, Dropbox, Instagram, and Instagram. Learn how Python programmers use data to create visual representations that are easy to analyse and examine. Seaborn, a Python data-visualization library, will be introduced to you in this course. Seaborn is a combination of aesthetic appeal and the technical insights of the Python programming language. Learn how to identify line, scatter, and other relational plots as well as the differences between them. What is the purpose of Python's categorical and quantitative variables? The programming language can visualise categorical data, which has a fixed length, and quantitative data that can be measured. Learn how to categorise plots, and other quantitative variables in data visualisation.

The course's final section will cover the basics of uncertainty in visualisations. The course will cover uncertainty in data, point estimation intervals, confidence bands, and other aspects of uncertainty. You'll learn how to use your new knowledge to confidently show uncertainty in data. You can preview some of the course steps here before you sign up.

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Total Duration

4 weeks

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Level

Advanced

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Learn Type

Certifications

Data Visualisation with Python: Bokeh and Advanced Layouts

The first week of this course will cover the main functions of Bokeh as well as how it can be used for interactive visualisations. Bokeh's advantages over other data visualization packages will be discussed. You'll also learn about the Python concept of Glyphs and how they can customized. After you have mastered the basics, you will learn more about Bokeh's plot layouts and advanced features. You will be able to link sliders to plots using selects. Week three will be a full-fledged exploration of data analysis. Learn about the different phases of data exploration, as well as data ethics and responsible storytelling. The course will also allow you to combine all your knowledge with extended data analysis and visualization. The final week will focus on data analytics as an emerging field and the role of DataOps, UX design and other technologies that can improve your prospects as a data professional. You'll be able to participate in practical exercises and perform real-world tasks throughout the course that will put you in the position of a data analyst at a streaming service. You can see some of the steps in this course before you sign up.

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