Python for Business Data Analytics and Intelligence

Become a top Business Data Analyst. We’ll teach you everything you need to go from a complete beginner to getting hired as an analytics professional. You’ll learn to use Python and the latest industry tools and techniques to make data-driven decisions.

This course includes:

  • Access to exclusive ZTM community
  • Certificate of Completion
  • Beginner, intermediate and advanced topics and tools
  • Unlimited access to all courses, workshops, career paths and resources
 15 hours of video 25 + bonus resources


  • Basic Python knowledge. Don’t know Python? You’ll get access to our Python Bootcamp as well
  • A computer (Windows, Mac, or Linux) with an internet connection


  •  The skills to become a professional Business Analyst and get hired
  •  Step-by-step guidance from an industry professional
  •  Learn to use Python for statistics, causal inference, econometrics, segmentaiton, matching, and predictive analytics
  •  Master the latest data and business analysis tools and techniques including Google Causal Impact, Facebook Prophet, Random Forest and much more
  •  Participate in challenges and exercises that solidify your knowledge for the real world
  •  Learn what a Business Analyst does, how they provide value, and why they’re in demand
  •  Analyze real datasets related to Moneyball, wine quality, Wikipedia searches, employee remote work satisfaction, and more
  •  Learn how to make data-driven decisions
  •  Enhance your proficiency with Python, one of the most popular programming languages
  •  Use case studies to learn how analytics have changed the world and help individuals and companies succeed

What is business data analytics? Why learn business analytics? What does a business data analyst do?

Glad you asked!

We now live in a data-driven economy and companies around the world are in a race to make the best data-driven decisions.

Enter Business Data Analysts (future you!).

Being a Business Analyst is like being a detective.

You use tools (like Python, Facebook Prophet, Google Causal Impact) to investigate and analyze data to understand the past and predict what is most likely to happen in the future. From there, you’ll determine the best course of action to take.

Companies need these Analysts because they’re able to turn data into $$$.

They use the tools and techniques (that we teach you in this course) to quickly interpret and analyze data and turn it into actionable information and insights. These insights are relied upon to make key business decisions.

And making the right decision can be difference between gaining or losing millions of dollars.

That’s why people with these data analysis skills are extremely in-demand. And why companies are willing to pay great salaries to attract them.

Using the latest industry techniques, this business data analytics course is focused on efficiency. So you never have to waste your time on confusing, out-of-date, incomplete tutorials anymore.

You’ll learn by doing by completing exercises and fun challenges using real-world data. This will help you solidify your skills, push you beyond the basics and ensure that you have a deep understanding of each topic and feel confident using your new skills on any project you encounter.

And unlike other online courses and tutorials, you won’t be learning alone.

Because by enrolling today, you’ll also get to join our exclusive live online community classroom to learn alongside thousands of students, alumni, mentors, TAs and Instructors.

Most importantly, you’ll be learning from an industry professional (Diogo) that has actual real-world experience as a Business Data Analyst. He teaches you the exact tools and techniques he uses in his role.

Finally, this course will be constantly updated as the landscape changes.

Just as the business data analytics & business intelligence ecosystems evolve, we will ensure this course is constantly updated with new lectures and resources so that you will stay at the top of your field.

This course will be your go-to place to get all the latest analytics best practices anytime in the future.

Here’s a section by section breakdown of what you’ll learn in this course:

The curriculum is very hands-on. But you’ll still be walked through everything step-by-step, so even if you have limited knowledge in statistics and Python, you’ll have no problems getting up to speed.

We start from the very beginning by teaching you the fundamental building block of data analytics: statistics with Python.

But we don’t stop there.

We’ll then dive into advanced topics so that you can make good, analytical decisions and know which tools in your toolbox are right for any project.

1. Basic & Intermediary Statistics with Python – Statistics are the basis of analytics and are critical for analytical thinking. Even basic concepts like Mean, Standard Deviation, and Confidence Interval will be a game-changer in helping you interpret, challenge, and present your arguments and reasoning in the professional world.

You’ll also learn how to calculate all this and more using one of the world’s most popular programming languages: Python.

This section will also lay the foundation for you to understand the more advanced analytics concepts.

2. Linear, Multilinear, & Logistic Regression – You’ll learn how and why to use Python for the most commonly used type of predictive analysis: regression.

The idea of regression is to examine the relationship between certain variables, and it’s most commonly used in finance and investing, but it’s relevant for every sector (if you want to impress your boss, analyze a relationship using regression!).

3. Econometrics & Causal Inference – Now you’ll start learning more advanced topics. Econometrics & Causal Inference may sound scary, but they are probably the most important concepts for you to master to become a top Business Analyst.

They help you answer all sorts of problems using analytics and most importantly you’ll be a better decision maker once you learn to use them. You will learn how to tackle biases, like the omitted variable bias or the self-selection bias, which are biases that companies very commonly fall victim too.

Once you know how to these concepts to help you find the solutions, you’ll also learn how to better spot the problems.

4. Google Causal Impact – Now we’ll start using some of the key tools that the real-world professionals use, starting with Google Causal Impact, an open-source package for estimating causal effects in time series.

How can we measure the number of additional clicks or sales that a digital ads campaign generated? How can we estimate the impact of a new feature on your app downloads?

In principle, these questions can be answered through causal inference. But in practice, estimating a causal effect accurately is hard, especially when a randomised experiment is not available. Thankfully, we can use Google Causal Impact to make causal analyses simple and fast.

5. Matching – Here you’ll learn how to use data matching to compare data stored in different systems in and across organizations, helping you reduce data duplication and improve data accuracy. By the end, you’ll know exactly when and how to use data matching to efficiently match and compare data.

6. RFM (Recency, Frequency, Monetary) Analysis – In this section, you’ll learn about a marketing technique called RFM Analysis. It’s used to quantitatively rank and group customers based on the recency, frequency and monetary total of their recent transactions to identify the best customers and perform targeted marketing campaigns.

Course link :

Course size : 2GB


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