AI Applications for Business Success

with Horia Mărgărit

4.7/5

(151)

This course will introduce you to the challenges and opportunities of supply chain analytics to then show you how to leverage the power of AI to meet your business goals.

2 hours 27 lessons

Start course

Course Overview

AI isn’t just a fancy concept that powers self-driving vehicles, robots, and high-tech companies. Most organizations – regardless of their size and industry – can benefit from the application of artificial intelligence. In this course, you’ll get an overview of business analytics and find out how to define SMART goals and conduct SWOT analysis. You’ll go through the challenges and opportunities of supply chain analytics to then determine the business problem we’ll tackle throughout the course.

27 High Quality Lessons

1 Practical Tasks

2 Hours of Video

Certificate of Achievement

Topics covered

Business analyticsCareer developmentdata analysismachine learningPythonTheory

What You'll Learn

This course will give you insight into the workings of a supply chain business model. You’ll learn how to analyze and define business goals, and then explore ways of incorporating AI and ML models into every step of the process to improve your business operations.

Understand and define SMART Goals

Perform a SWOT analysis

Become familiar with modern AI techniques

Discover how to use AI to infer causation

Make better and faster decisions using data

Yield the desired results in your strategic business objectives

Curriculum

Introduction Free

2 Lessons 5 Min

This is the intro to the course. We give you a taste of what you’ll learn throughout the course, as well as a step by step of what’s to follow in each of the following sections.
What Does the Course Cover Free Course Resources Free
Business Goals Free

6 Lessons 25 Min

Here we introduce the case study we’ll follow throughout the course and define our business goal, or SMART goal. We also do a SWOT analysis and discuss main problems in Business Analytics.
Introduction to the business case Free SWOT Analysis Free SMART Goals Free Limitations of the BI Approach Free Correlation vs. Causation Free Making Recommendations with Descriptive Statistics Free
Approaches to solving the business objective Free

4 Lessons 15 Min

Here we take a look at how a Business Intelligence analyst might tackle the problem, and see the limitation of the BI approach. We’ll also start discussing shadow manifolds and Taken’s theorem.
Introduction to the approaches Free The BI Approach Free State Space and Takens' Theorem Free Shadow Manifolds and K-Nearest Neighbors Free
Artificial Intelligence in Business Free

12 Lessons 78 Min

This is the main body of the course. Here, we delve into topics starting from Attainability, then, we go through techniques Convergent Cross Mapping – which is where the power of AI to infer causality lies. We also dedicate time to SHAP values and LIME to evaluate the performance of a model.
Quantifying Attainability Free Gradient Boosted Machines: Part 1 Free Gradient Boosted Machines: Part 2 Free Gradient Boosted Machines: Part 3 Free SHAP Values Free Friedman's H-Statistic Free LIME Free Waterfall Charts 1 Free Waterfall Charts 2 Free Causation: Traditional Statistical Methods Free Causation: Advanced Statistical Methods Free Time Series Forecasting with Takens' Theorem Free
Artificial Intelligence Recommends Metrics

3 Lessons 12 Min

In this section, we devote time to parametric tests and designing a hybrid experiment. In other words, we discuss how we can show if the recommended metrics by our AI model, have actually generated the change we see in metrics.
Introduction The Hybrid Experiment Quantile Difference Tests

Student feedback

4.7/5

151 ratings

5 stars

120 (79%)

4 stars

21 (14%)

3 stars

9 (6%)

2 stars

0 (0%)

1 star

1 (1%)

Emmanuel Odunayo

31.10.2022

This is my first advanced specialisation course and I really appreciate the thorough advanced statistics provided. That being said the lecturer must be nearer to the mic when doing his recordings as well as be a bit more enthusiastic ( I dont know how but data science should be taught more thought provoking or a subtle change of tone from time to time as opposed to the monotone voice ive heard throughout all these lectures). The code is outdated in the git hub and the preliminary stages of running those codes in Github did not work. Lecture notes would useful as I am patient enough to use the subtitles and pick out what I assume (I am guessing) is the most important statistical knowledge from the course. The courses before had pdf files to explain statistics and they are very helpful for data science students globally.

Rosaline Pahud de Mortanges

23.09.2022

I would love to translate the subtitle to Dutch or at least have subtitles in english, then I can speed up, the video, because the voice over is really boring to listen to and it causes me, that I switch over to other websites. The topic about the swot analysis and smart goals is great but what has it really to do with data science. The best way to find a business case is to understand the core processes, so i guess that is the goal?