15+ Best Business Analytics Courses & Certifications in 2024
What is the key to strategic decision making today? test
Since most businesses today handle some form of data, learning how to use statistical methods and technologies to analyze this will enable you to gain new insights which can drive your decision making endeavors.
This is particularly handy if you are able to combine the various forms of business analytics like descriptive analytics, predictive analytics, as well as prescriptive analytics.
In this article, we are going to check out some of the best business analytics courses and certifications online to get you started learning today.
By taking these business analytics courses online, you’ll become an expert in the statistics of data science and business analysis.
In addition to that, you’ll also learn the business analysis foundations, like process modeling, that will prepare you for the Certified Analytics Professional certification.
So let’s get started.
Here is a detailed summary of what you’ll learn in each of these business analytics courses on Coursera.
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
1. Marketing Analytics
As you already know, organizations large and small are inundated with data about consumer choices.
But one thing that is for sure is, that wealth of information does not always translate into better decisions.
Knowing how to interpret data is the challenge, and marketers in particular are increasingly expected to use analytics to inform and justify their decisions.
Marketing analytics enables marketers to measure, manage, and analyze marketing performance to maximize their effectiveness and optimize return on investment (ROI).
Beyond the obvious sales and lead generation applications, marketing analytics can offer profound insights into customer preferences and trends, which can be further utilized for future marketing and business decisions.
This business analytics course on Coursera, developed at the Darden School of Business at the University of Virginia, gives you the tools to measure brand and customer assets, understand regression analysis, and design experiments as a way to evaluate and optimize marketing campaigns.
By the end of this course, you’ll have a solid understanding of how to use marketing analytics to predict outcomes and systematically allocate resources.
Rating: 4.6 stars (4, 863 ratings).
Level: Beginner.
Students: 217, 911.
Duration: 16 hours.
Language: English.
2. Customer Analytics
Did you know that data about our browsing and buying patterns are everywhere?
From credit card transactions and online shopping carts to customer loyalty programs and user-generated ratings/reviews.
There is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions.
In this course for business analytics on Coursera, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics:
- Descriptive analytics
- Predictive analytics
- Prescriptive analytics
…and their application to real-world business practices including Amazon, Google, and Starbucks to name a few.
This best selling course on Coursera provides an overview of the field of analytics so that you can make informed business decisions.
It is an introduction to the theory of customer analytics and is not intended to prepare you to perform customer analytics.
By the end of this course, you’ll be able to:
Describe the major methods of customer data collection used by companies and understand how this data can inform business decisions.
Additionally, describe the main tools used to predict customer behavior and identify the appropriate uses for each tool.
Not only will you communicate key ideas about customer analytics and how the field informs business decisions, but you will also communicate the history of customer analytics and the latest best practices at top firms.
Rating: 4.6 stars (9, 372 ratings).
Level: Beginner.
Students: 186, 418.
Duration: 12 hours.
Language: English.
3. Business Metrics for Data-Driven Companies
In this business analytics course on Coursera, you will learn best practices for how to use data analytics to make any company more competitive and more profitable.
Additionally, you will be able to recognize the most critical business metrics and distinguish them from mere data.
But that’s not all, as you’ll also get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies.
And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs.
Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture.
Digital companies like Amazon, Uber, and Airbnb are transforming entire industries through their creative use of big data.
So it’s only right if you understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies.
Rating: 4.6 stars (7, 155 ratings).
Level: Beginner.
Students: 194, 434.
Duration: 9 hours.
Language: English.
4. Fundamentals of Visualization with Tableau
In this first course of this specialization, you will discover what data visualization is, and how we can use it to better see and understand data.
Using Tableau, you’ll examine the fundamental concepts of data visualization and explore the Tableau interface, identifying and applying the various tools Tableau has to offer.
By the end of the course, you will be able to prepare and import data into Tableau and explain the relationship between data analytics and data visualization.
This course is designed for you if you have never used Tableau before or may need a refresher or want to explore Tableau in more depth.
No prior technical or analytical background is required.
The course will guide you through the steps necessary to create your first visualization from the beginning based on data context, setting the stage for you to advance to the next course in this Specialization. For this reason, this course is qualified to be here on the list of the best Coursera courses for business analytics.
Rating: 4.5 stars (4, 293 ratings).
Level: Beginner.
Students: 94, 427.
Duration: 10 hours.
Language: English.
5. Introduction to Data Analytics for Business
This course for business analytics on Coursera will expose you to the data analytics practices executed in the business world.
You will explore such key areas as the analytical process, how data is created, stored, accessed, and how the organization works with data and creates the environment in which analytics can flourish.
What you learn in this course will give you a strong foundation in all the areas that support analytics.
And will also help you to better position yourself for success within your organization.
You’ll develop skills and a perspective that will make you more productive faster while allowing you to become a valuable asset to your organization.
This course also provides a basis for going deeper into advanced investigative and computational methods, which you have an opportunity to explore in future courses of the Data Analytics for Business specialization.
Rating: 4.7 stars (1, 967 ratings).
Level: Beginner.
Students: 105, 429.
Duration: 11 hours.
Language: English
6. Python and Statistics for Financial Analysis
Did you know that python is now becoming the number 1 programming language for data science?
If you are interested in Python, you can check out my other article where I reviewed 11 Best Python Courses On LinkedIn Learning To SignUp For.
Due to python’s simplicity and high readability, it is gaining importance in the financial industry.
This business analytics course on Coursera combines both python coding and statistical concepts and applies to analyze financial data, such as stock data.
By the end of the course, you can achieve the following using python:
- Import, pre-process, save, and visualize financial data into pandas Dataframe.
- Manipulate the existing financial data by generating new variables using multiple columns.
- Recall and apply the important statistical concepts (random variable, frequency, distribution, population and sample, confidence interval, linear regression, etc. ) into financial contexts.
- Build a trading model using multiple linear regression models.
- Evaluate the performance of the trading model using different investment indicators.
Jupyter Notebook environment is also configured in the course platform for practicing python coding without installing any client applications.
Since this course provides you with detailed information about python and statistics for financial analysis, it deserves a seat here as one of the best courses for business analytics on Coursera.
Rating: 4.4 stars (1, 902 ratings).
Level: Intermediate.
Students: 62, 699.
Duration: 13 hours.
Language: English.
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7. Foundations of strategic business analytics
This business analytics course on Coursera is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts.
You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language, and… are familiar with databases and data analysis techniques such as regression, classification, and clustering.
However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data, and explore new features and statistical functions in R.
The instructors will discuss a wide variety of applications of Business Analytics. From Marketing to Supply Chain or Credit Scoring and HR Analytics, etc.
They will also cover many different data analytics techniques, each time explaining how to be relevant for your business.
Additionally, they will also present you with different data analytics tools to be applied to different types of issues.
By doing so, you’ll develop four sets of skills needed to leverage value from data which also makes this course another best Coursera course for business analytics:
- Analytics.
- IT.
- Business.
- Communication.
Rating: 4.4 stars (553 ratings).
Level: Intermediate.
Students: 43, 437.
Duration: 9 hours.
Language: English.
8. Business Analytics for Decision Making
In this Coursera course for business analytics, you will learn how to create models for decision making.
You will start with cluster analysis, a technique for data reduction that is very useful in market segmentation.
Then, you’ll move to learn the basics of Monte Carlo simulation that will help you model the uncertainty that is prevalent in many business decisions.
A key element of decision making is to identify the best course of action.
Since business problems often have too many alternative solutions, you will learn how optimization can help you identify the best option.
What is really exciting about this best selling business analytics course is that you won’t need to know a computer language or advanced statistics to learn about these predictive and prescriptive analytic models.
The Analytic Solver Platform and basic knowledge of Excel are all you’ll need.
If you take this course, you will be able to get free access to the Analytic Solver Platform.
Rating: 4.6 stars (1, 178 ratings).
Level: Intermediate.
Students: 51, 739.
Duration: 9 hours.
Language: English.
9. Case studies in business analytics with ACCENTURE
This Coursera course for business analytics is restricted to learners enrolled in Strategic Business Analytics specialization as a preparation for the capstone project.
During the first two MOOCs, the instructors focused on specific techniques for specific applications.
The main objective of this course is to give you a helicopter overview of what’s happening in this field.
You will see how the tools presented in the two previous courses of the Specialization are used in real-life projects.
In this course, the instructors want to ignite your reflection process.
Hence, you will best make use of the Accenture cases by watching first the MOOC and then investigate by yourself on the different concepts, industries, or challenges that are introduced during the videos.
By the end of this course, you will be able to:
- Identify the possible applications of business analytics.
- Reflect on the possible solutions and added-value applications that could be proposed for their capstone project.
The cases in this course are presented by senior practitioners from Accenture with different backgrounds in terms of industry, function, and country.
Finally, special attention will be paid to the “value case” of the issue raised to prepare you for the capstone project of the specialization.
Rating: 3.7 stars (184 ratings).
Level: Intermediate.
Students: 20, 009.
Duration: 10 hours.
Language: English.
10.Introduction to Business Analytics: Communicating with Data
This course for business analytics on Coursera introduces you to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space.
The goal of this course is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives.
You will learn to identify the ideal analytic tool for their specific needs.
Furthermore, you will understand valid and reliable ways to collect, analyze, and visualize data.
But there’s more, you will also utilize data in decision making for their agencies, organizations, or clients.
This course is one of the best courses for business analytics on Coursera because it gives you detailed information about communicating with data.
Rating: 4. 6 stars (377 ratings).
Level: Intermediate.
Students:20, 891.
Duration: 14 hours.
Language: English.
11. Supply Chain Analytics
A supply chain is a complex system with conflicting objectives of cost efficiency and customer satisfaction.
Supply chain management is becoming increasingly data-driven. Through the real-life story and data of a major US telecommunication company.
You will learn the analytics tools/skills to diagnose and optimize a supply chain.
And upon completion of this business analytics course, you will be able to:
- Use data analytics to assess the impact of various strategies on all aspects of a supply chain, from inventory, shipping, warehouse order fulfillment, store operations, and customer satisfaction.
- Customize the supply chain strategy by product to improve the overall cost efficiency without sacrificing customer service.
- Obtain hands-on experience on the application and financial impact of analytics in integrated supply chain and logistics planning.
Rating: 4.7 stars (522 ratings).
Level: Beginner.
Students: 12, 088.
Duration: 9 hours.
Language: English.
Conclusion
Before data can be analyzed, it must be collected, centralized, and cleaned to avoid duplication, and filtered to remove inaccurate, incomplete, and unusable data.
With the help of these best business analytics courses on Coursera, you will be able to perform all these tasks and even get a certificate at the end.
But that’s not all, you will also have the perfect skills that will make you get hired in this lucrative field or get a promotion in case you are already a working professional.
Here is a summary of what you’ll learn and do in these courses:
- Obtain hands-on experience on the application and financial impact of analytics in integrated supply chain and logistics planning.
- Identify the possible applications of business analytics.
- Learn how to create models for decision making.
- Describe the major methods of customer data collection used by companies and understand how this data can inform business decisions.
I hope these Coursera courses for business analytics help you learn the ins and outs of business analytics and launch a successful career in this lucrative field.
Have you ever taken any of these best Coursera courses for business analytics before?
If yes, please share your experience in the comments below.
