AI Applications for Business Success

with Horia Mărgărit
4.7/5
(354)

Leverage AI for business success: enhance supply chain efficiency and solve critical challenges

2 hours of content 4366 students

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 2 hours of content
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

AI Applications for Business Success

A course by Horia Mărgărit

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 2 hours of content
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

$99.00

Lifetime access

Buy now

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 2 hours of content
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

What You Learn

  • Master the SMART goals framework to effectively define and implement specific, measurable, achievable, relevant, and time-bound business objectives
  • Perform SWOT analysis to deeply understand business challenges before designing suitable data-driven solutions
  • Discover how to use advanced AI techniques to infer causation
  • Boost your business acumen by gaining a thorough understanding of supply chain processes and key value drivers
  • Master hybrid experiments to evaluate whether AI-proposed solutions generate business value
  • Advance your technical data science skills to impress hiring managers and recruiters

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

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.

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What Does the Course Cover

1.1 What Does the Course Cover

5 min

Course Resources

1.2 Course Resources

1 min

Introduction to the business case

2.1 Introduction to the business case

2 min

SWOT Analysis

2.2 SWOT Analysis

5 min

SMART Goals

2.3 SMART Goals

7 min

Limitations of the BI Approach

2.4 Limitations of the BI Approach

4 min

Curriculum

  • 1. Introduction
    2 Lessons 6 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
    5 min
    Course Resources Read now
    1 min
  • 2. Business Goals
    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
    2 min
    SWOT Analysis
    5 min
    SMART Goals
    7 min
    Limitations of the BI Approach
    4 min
    Correlation vs. Causation
    5 min
    Making Recommendations with Descriptive Statistics
    2 min
  • 3. Approaches to solving the business objective
    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
    5 min
    The BI Approach
    2 min
    State Space and Takens' Theorem
    4 min
    Shadow Manifolds and K-Nearest Neighbors
    4 min
  • 4. Artificial Intelligence in Business
    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
    6 min
    Gradient Boosted Machines: Part 1
    6 min
    Gradient Boosted Machines: Part 2
    4 min
    Gradient Boosted Machines: Part 3
    9 min
    SHAP Values
    9 min
    Friedman's H-Statistic
    7 min
    LIME
    9 min
    Waterfall Charts 1
    5 min
    Waterfall Charts 2
    5 min
    Causation: Traditional Statistical Methods
    4 min
    Causation: Advanced Statistical Methods
    6 min
    Time Series Forecasting with Takens' Theorem
    8 min
  • 5. 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
    3 min
    The Hybrid Experiment
    4 min
    Quantile Difference Tests
    5 min

Topics

TheoryPythonCareer developmentBusiness analyticsmachine learningdata analysis

Tools & Technologies

python

Course Requirements

  • You need to complete an introduction to Python before taking this course
  • Basic skills in statistics, probability, and linear algebra are required
  • It is highly recommended to take the Machine Learning in Python course first
  • You will need to install the Anaconda package, which includes Jupyter Notebook

Who Should Take This Course?

Level of difficulty: Advanced

  • Aspiring data scientists
  • Existing data scientists who want to improve their technical and domain-specific skills

Exams and Certification

A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Exams and certification

Meet Your Instructor

Horia Mărgărit

Horia Mărgărit

Director Data Science at

1 Courses

354 Reviews

4366 Students

Horia Margarit has a demonstrated history of success in the field of data science. Ever since earning dual Bachelor’s degrees in Cognitive and Computer Science from UC Berkeley and a Master’s degree in Statistics from Stanford University, Horia has managed to embark on an exciting career path involving data scientist roles at companies like ask.com, Intuit, Qubole, Autodesk, and Booster Fuels. With over 10 years of professional experience in the San Francisco Bay Area, he has differentiated himself by applying highly novel methods and approaches to tackling complex business problems. His predictions for business applications of AI have been featured in both CIO Magazine and Forbes. Horia’s primary focus is on technical underpinnings that maximize actual business and customer value.

What Our Learners Say

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24.11.2024

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