Do you want to learn Data Science?
My guess is that you are either a beginner looking to start from scratch or you are already a professional looking for a way to even get better at what you do, or maybe you are trying to secure a higher position at your current workplace.
All this can be achieved by just enrolling for some of the best Data Science courses on LinkedIn Learning.
When I look online, all I see is a bunch of wannabe tutors who just want to waste you. So in this article, I’ve collected the best LinkedIn Learning courses for Data Science that will give you all the basics you deserve.
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But not only will they give you basics but they will also give you skills and make you the talk of town leaving your boss no option but to promote you.
And since I’m here to help your online study a success, if you are interested in being an all-round professional, you should check my other article where I reviewed the best Ethical Hacking courses on PluralSight.
Okay, let’s get into it.
Here are some quick links to these courses on LinkedIn Learning…
Here is a detailed summary of what you’ll learn in each of these Data Science courses on LinkedIn.
We’ll look at what each course is about, what you’ll be able to do after the course as well as the requirements and skill level you need to have before starting any of these courses
Every person who works with data has to perform analytics at some point.
This popular course on LinkedIn Learning for Data Science, dramatically expanded and enhanced for 2018, teaches analysts and non-analysts alike the basics of data analytics and reporting.
Robin Hunt, the Instructor, defines what data analytics is and what data analysts do.
She then shows you how to identify your data set, including the data you don’t have. Plus you’ll also interpret and summarize data.
She also shows you how to perform specialized tasks such as:
- Creating workflow diagrams
- Cleaning data
- Joining data sets for reporting
This coverage continues with best practices for data analytics projects, such as verifying data, conducting effective meetings, and common mistakes to avoid.
But if you think that’s all, then, news flash! you’ll also learn techniques for repurposing, charting, and pivoting data.
Plus, you’ll get helpful productivity-enhancing shortcuts and troubleshooting tips for the most popular data analytics program, Microsoft Excel.
This is a FREE course.
Students: 300, 539.
Duration: 1 hour 39 minutes.
The career opportunities in data science, big data, and data analytics are growing dramatically.
If you’re interested in changing career paths, determining the right course of study, or deciding if certification is worth your time, this best Data Science course on LinkedIn is for you.
Jungwoo Ryoo is a professor of information science and technology at Penn State.
In this Data Science course, he reviews the history of data science and its subfields, he also explores the marketplaces for these fields, and reveals the five main skills areas:
- Data mining
- Machine learning
- Natural language processing (NLP)
This leads to an interesting discussion about the five biggest career opportunities, the six leading industry-recognized certifications available, and the most exciting emerging technologies.
Along the way, Jungwoo also discusses the importance of ethics and professional development. He also provides you with pointers to online resources for learning more.
Students: 139, 383.
Duration: 1 hour 12 minutes.
Statistics is not just the realm of data scientists.
Did you know that all types of jobs use statistics?
Statistics are important for making decisions, new discoveries, investments, and predictions.
Whether the subject is political races, sports rankings, shopping trends, or healthcare advancements, statistics is an instrument for understanding your favorite topic at a deeper level.
Professor Eddie Davila covers statistics basics, like calculating averages, medians, modes, and standard deviations.
He also shows you how to use probability and distribution curves to inform decisions, and how to detect false positives and misleading data.
Each concept in this course for Data Science on LinkedIn is covered in simple language, with detailed examples that show you how statistics are used in real-world scenarios from the worlds of:
… and more.
These techniques will help you understand your data, prove theories, and save time, money, and other valuable resources, all by understanding the numbers.
Students: 139, 793.
Duration: 2 hours 6 minutes.
Statistics are a core skill for many careers.
Basic stats are critical for making decisions, new discoveries, investments, and even predictions.
But sometimes you need to move beyond the basics. Statistics Fundamentals – Part 2 takes business users and data science mavens into practical, example-based learning of the intermediate skills associated with statistics: samples and sampling, confidence intervals, and hypothesis testing.
Eddie Davila first provides a bridge from Part 1, reviewing introductory concepts such as data and probability, and then moves into the topics of:
- Random samples
- Sample sizes
- Sampling error and trustworthiness
- The central unit theorem
- Confidence intervals (including explaining unexpected outcomes)
- Hypothesis testing
This qualifies this course as one of the best Data Science courses on Linked Learning.
This Data Science course on LInked Learning is a must for those working in data science, business, and business analytics, or anyone else who wants to go beyond means and medians and gain a deeper understanding of how statistics work in the real world.
Students: 86, 002.
Duration: 1 hour 56 minutes.
As you may already know, many stock market trades are now conducted with algorithms: computer programs that buy or sell stocks according to mathematical formulas.
These trades are conducted at a speed and frequency that is hard for humans to replicate.
Therefore, it’s important for finance professionals, and indeed everyone who invests in the stock market, to know how these algorithms work.
This LinkedIn course for Data Science shows you how to develop a back-tested, rules-based trading strategy, and program a simple trading algorithm of your own.
Professor Michael McDonald provides you with a brief primer on securities markets.
He explains how data helps investors forecast performance and automate trading.
Then he moves into the practical steps: coming up with algorithmic trading rules and developing and testing an algorithm.
Finally, he shows you how the algorithm can be applied and eventually expanded to other securities.
Since this course covers the algorithm in details, it qualifies as the best Data Science course.
Anyone working in financial services, or interested in investing in the stock market, will be able to use these tutorials to understand and develop simple trading algorithms of their own.
Students: 79, 863.
Duration: 1 hour 29 minutes.
Data science is driving a world-wide revolution that touches everything from business automation to social interaction.
It’s also one of the fastest-growing, most rewarding careers, employing analysts and engineers around the globe.
This course for Data Science on LinkedIn Learning provides an accessible, non-technical overview of the field, covering the vocabulary, skills, jobs, tools, and techniques of data science.
Instructor Barton Poulson defines the relationships to other data-saturated fields such as machine learning and artificial intelligence.
If you are interested in learning more about Machine Learning courses, then you should check out my other article where I reviewed the best Machine Learning courses.
He reviews the primary practices like:
- Gathering and analyzing data
- Formulating rules for classification and decision-making
- Drawing actionable insights
Additionally, he also discusses ethics, accountability and provides direction to learn more.
By the end of this best data science course on LinkedIn, you’ll see how data science can help you make better decisions, gain deeper insights, and make your work more effective and efficient.
Students: 96, 001.
Duration: 1 hour 29 minutes.
With this Data Science course, you will gain insight into key statistical concepts and build practical analytics skills using Python and powerful third-party libraries.
Instructor Michele Vallisneri covers several major skills including:
- Describing data
- Statistical inference
- Statistical modeling.
All concepts are introduced by analyzing intriguing real-world datasets and discussed from a machine-learning perspective, which assumes that powerful computation can replace complex mathematics.
The instructor will teach you how to install and set up Python.
Additionally, you’ll learn how to describe distributions and categorical variables.
By the end of this best selling Data Science course on Linked Learning, you will have learned importing and cleaning data, using basic statistical inference and modeling techniques, and also Bayesian inference.
Students: 56, 827.
Duration:2 hours 58 minutes.
Python for Data Science Essential Training is one of the most popular data science courses at LinkedIn Learning.
It has now been updated and expanded to two parts, for even more hands-on experience with Python.
In this Data Science course, instructor Lillian Pierson takes you step by step through a practical data science project: a web scraper that downloads and analyzes data from the web.
Along the way, she introduces techniques to:
- Describe raw data
- Generate visualizations
- Remove outliers
- Perform simple data analysis
- Generate interactive graphs using the Plotly library
You should walk away from this course with basic coding experience that you can take to your organization and quickly apply to your own custom data science projects.
Duration: 6 hours 2 minutes.
Statistics help us make sense of the world around us.
These numbers help everyone from political pollsters to fantasy football aficionados make informed calls based on the mountains of data at their disposal.
In this weekly series, you will learn how to decode the statistics that pop up on a daily basis.
Eddie Davila explores a new eclectic, real-world topic each week.
You will also learn how stats are used to find the average score on a test.
And finally, this course for Data Science on LinkedIn will teach you how casinos use stats to ensure that the house will usually win, so if you are a gambling type of guy, then this course will give you some 1 or 2 secrets to add in your box.
Note: Because this is an ongoing series, you will not receive a certificate of completion.
Students: 36, 003.
Duration: 4 hours 33 minutes.
This best Data Science course on LinkedIn Learning gives you a chance to discover how to quickly glean insights from your data using Power BI.
This formidable set of business analytics tools, which includes the Power BI service, Power BI Desktop, and Power BI Mobile, can help you more effectively to create and share impactful visualizations with others in your organization.
In this LinkedIn course for Data Science, Gini von Courter helps you get started with this powerful toolset.
Gini begins by covering the web-based Power BI service, explaining how to import data, create visualizations, and arrange those visualizations into reports.
Furthermore, she discusses how to pin visualizations to dashboards for sharing, as well as how to ask questions about your data with Power BI Q&A.
She also provides coverage of Power BI Mobile and shows you how to use the data modeling capabilities in Power BI Desktop.
This is a FREE course.
Level: Beginner + Intermediate.
Students: 51, 539.
Duration: 3 hours 20 minutes.
Data isn’t valuable until you put it to good use.
Statistics transforms data into meaningful information, enabling organizations to make better decisions and predictions.
That’s why statistics collecting, analyzing, and presenting data is a valuable skill for anyone in business or academia.
In this Data Science course on LinkedIn, Joseph Schmuller teaches the fundamentals of descriptive and inferential statistics and shows you how to apply them in Microsoft Excel. An inexpensive and accessible application that offers an array of powerful statistical tools.
Using the built-in functions and charts, along with the Analysis Toolpak add-on, Joe explains how to:
- Organize and present data
- Understand sampling distributions
- Test hypotheses
- Draw conclusions
He also covers probabilities, averages, variability, distribution, estimation, variance, regression testing, and more.
By the end of this best Data Science course on LinkedIn Learning, you should be able to fully understand and apply basic statistical concepts to a wide variety of data.
This is a FREE course.
Level: Beginner + Intermediate.
Students: 32, 832.
Duration: 3 hours 37 minutes.
With these best Data Science courses on LinkedIn Learning, you too can master the terms, formulas, and techniques needed to perform the most common types of statistics.
Still not convinced?
These LinkedIn courses for Data Science will help you get a better shot at job prospects, boast about your skills on your resume or portfolio, and also make a transition in career pathways.
Here is a summary of what you’ll learn from these courses:
- How to organize and present data
- Basic coding experience that you can take to your organization
- Programming a simple trading algorithm of your own
- How to use probability and distribution curves to inform decisions
- How stats are used to find the average score on a test
I hope these Data Science courses on LinkedIn Learning help you launch a successful career in Data Science, or at least make you better at your current job.
Have you ever taken any of these best Data Science courses on LinkedIn before?
If yes, please share your experience in the comments.