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Generative AI, ChatGPT, Copilot & AI Agents Masterclass 2025

4.6 Filled star Filled star Filled star Filled star Half star
Based on 1,343 ratings
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Dr. Ryan Ahmed, Ph.D., MBA and Stemplicity Inc.

This course is designed to unlock the potential of Generative AI and Microsoft Copilot to transform business processes, enhance decision-making, and drive innovation. This comprehensive course equips professionals with cutting-edge skills to harness AI tools such as ChatGPT, Gemini, Claude, DeepSeek, and Microsoft Copilot for a wide range of business applications.

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This course is designed to unlock the potential of Generative AI and Microsoft Copilot to transform business processes, enhance decision-making, and drive innovation. This comprehensive course equips professionals with cutting-edge skills to harness AI tools such as ChatGPT, Gemini, Claude, DeepSeek, and Microsoft Copilot for a wide range of business applications.

Learn to train and fine-tune custom GPT models tailored to your company's unique data to automate workflows, generate actionable insights, and optimize operations. Master AI-driven techniques for data wrangling, cleaning, and visualization, using tools to create impactful bar charts, heatmaps, and time-series visualizations. Explore advanced methods like Z-score analysis and Isolation Forests to detect anomalies, monitor market trends, and enhance operational efficiency.

Dive deep into AI applications for financial analysis, including extracting insights from 10-K reports, sentiment analysis, and forecasting using sophisticated models like Gain expertise in building AI agents and leveraging CoPilot to streamline complex workflows across platforms like Excel, Word, PowerPoint, and Teams.

Throughout the course, learners will also simulate real-world scenarios to develop robust financial and strategic planning skills. Apply SWOT analysis, financial KPI assessments, and AI-powered tools for supply chain evaluation, marketing strategy optimization, and growth forecasting.

Whether you are looking to enhance your data analysis capabilities, automate routine tasks, or lead AI-driven innovation in your organization, this course provides the practical knowledge and hands-on experience you need to excel in today’s data-centric business environment.

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What's inside

Syllabus

Download the Course Materials
Module 1: Introduction to Generative AI
********Part A: Generative AI Fundamentals*********
Welcome to Part A: Generative AI Fundamentals
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Welcome to the "Introduction to Generative AI" Quiz! This quiz is designed to assess your understanding of key concepts covered in Module 1, including Artificial Intelligence (AI), Generative AI, ChatGPT, Microsoft Copilot, AI history, popular AI models, and top generative AI tools.

Through 10 multiple-choice questions, you will test your knowledge on:
       - The difference between AI and Generative AI
       - The capabilities and applications of ChatGPT and Microsoft Copilot
       - Key AI developments, including Artificial General Intelligence (AGI)
       - The impact of emerging AI tools like Deepseek and DALL·E
       - Real-world applications and challenges of AI in various industries

This quiz is a great opportunity to reinforce your learning and apply the concepts in practical scenarios.

Good luck!

This quiz is designed to assess your understanding of key concepts covered in Module 2: AI Deep Dive & Prompt Engineering Fundamentals. It includes questions on the fundamental components of AI, the AI training process, prompt engineering, and key AI terminologies.

By the end of this quiz, you should be able to:
    - Identify the core components of AI and their roles
    - Understand the different types of prompting techniques (zero-shot, few-shot, chain-of-thought)
    - Explain how transformers and self-attention mechanisms improve AI performance
    - Differentiate between system and user prompts in OpenAI API
    - Adjust AI model temperature settings to influence response creativity

Best of luck!

This 10-question quiz is designed to assess your understanding of key concepts covered in Module 3: Data Wrangling & Feature Engineering. The quiz covers Financial Planning and Analysis (FP&A), data wrangling techniques, Pandas library functions, feature engineering, and data preprocessing methods like normalization and one-hot encoding.

Through this quiz, you will:

- Test your knowledge of data wrangling concepts, including handling missing data, merging datasets, and using Pandas functions.

- Demonstrate an understanding of feature engineering, including encoding categorical variables and scaling data.

- Gain insights into real-world Financial Planning & Analysis (FP&A) use cases as they relate to data handling.

Good Luck!

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Covers a range of AI tools like ChatGPT, Gemini, Claude, and Microsoft Copilot, which are actively used in various industries for automation and insights
Explores AI applications in financial analysis, including extracting insights from 10-K reports and sentiment analysis, which are valuable skills in the finance domain
Includes hands-on projects involving data wrangling, cleaning, and visualization using Pandas, which are essential skills for data-driven decision-making
Introduces machine learning concepts and algorithms like decision trees and random forests, which are fundamental for financial forecasting and predictive modeling
Delves into competitor analysis using Generative AI, covering techniques like vector embeddings, LLM fine-tuning, and RAG, which are useful for strategic business planning
Focuses on specific tools and libraries, so learners should verify that the versions taught are still relevant and supported for their intended applications

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Reviews summary

Practical generative ai for business

According to learners, this course provides a highly practical and business-focused approach to Generative AI. Students appreciated the coverage of key tools like ChatGPT, Copilot, Gemini, and Claude, finding the hands-on projects and real-world examples particularly valuable for immediate application in their roles. The course structure is often described as clear and well-organized, with content feeling current and relevant for the 2025 landscape. However, some students noted that the course assumes a foundational understanding of certain technical concepts, particularly in data handling sections, which may require supplemental learning for absolute beginners.
Introduces ChatGPT, Copilot, Gemini, Claude.
"It wasn't just ChatGPT, but also showed Copilot and others."
"A good overview of the major AI players and their capabilities."
"Helped compare the different tool features and when to use them."
"Explores practical demos for various platforms which is very helpful."
Logical flow and clear explanations.
"The course was well-organized and easy to follow step-by-step."
"Lectures explained complex ideas clearly, making them accessible."
"Modules built nicely upon each other in a logical progression."
"The structure made learning the concepts straightforward and less intimidating."
Up-to-date for the 2025 field.
"The material felt very current and relevant for 2025 trends."
"Covered recent updates in AI tools which is crucial."
"Appreciated the focus on the latest agents and models available."
"Seems the instructor updates the content regularly to stay relevant."
Focuses on real-world business cases.
"The business examples were highly relevant to my daily tasks."
"I could immediately apply the techniques to my work."
"Loved how the course showed concrete ways to use AI in finance and marketing."
"The projects are grounded in realistic scenarios which makes learning effective."
Requires some coding or data basics.
"Some parts on data wrangling were tough without Python background."
"Assumes you know Pandas, which I didn't, needed external help."
"Wish it had a quick introductory module to the required coding skills."
"Needed to supplement some coding basics to fully follow along the projects."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Generative AI, ChatGPT, Copilot & AI Agents Masterclass 2025 with these activities:
Review Machine Learning Fundamentals
Solidify your understanding of machine learning basics to better grasp the AI-driven financial prediction models covered in the course.
Browse courses on Machine Learning
Show steps
  • Review key concepts like supervised and unsupervised learning.
  • Practice building simple regression models.
  • Familiarize yourself with common evaluation metrics.
Review 'Python for Data Analysis' by Wes McKinney
Strengthen your data manipulation skills with Pandas, a crucial tool for preparing data for Generative AI models.
View Python for Data Analysis on Amazon
Show steps
  • Read the chapters on Pandas DataFrames and Series.
  • Practice data cleaning and transformation techniques.
  • Work through the examples on data aggregation and grouping.
Build a Financial Dashboard with Sample Data
Apply your data visualization skills to create an interactive dashboard that showcases key financial metrics and insights.
Show steps
  • Gather sample financial data from public sources.
  • Choose a visualization tool like Tableau or Power BI.
  • Design and implement the dashboard with interactive elements.
  • Present your dashboard and explain your design choices.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Write a Blog Post on AI Applications in Finance
Deepen your understanding of AI in finance by researching and writing about real-world applications and use cases.
Show steps
  • Research current trends in AI for financial analysis.
  • Choose a specific application area, such as fraud detection or algorithmic trading.
  • Write a clear and concise blog post explaining the application and its benefits.
  • Include examples and case studies to illustrate your points.
Review 'Competing on Analytics' by Thomas Davenport
Gain insights into how businesses leverage analytics to gain a competitive edge, complementing the course's focus on AI-driven business applications.
View Competing on Analytics: Updated, with a New... on Amazon
Show steps
  • Read the chapters on analytical competition and strategy.
  • Identify examples of companies that have successfully used analytics.
  • Consider how the concepts apply to your own organization or industry.
Develop a Presentation on Ethical Considerations in AI
Explore the ethical implications of using AI in business and develop a presentation to raise awareness and promote responsible AI practices.
Show steps
  • Research ethical issues related to AI, such as bias and privacy.
  • Develop a presentation outline with key talking points.
  • Create visually appealing slides with relevant examples.
  • Practice your presentation and prepare for questions.
Contribute to an Open-Source AI Project
Enhance your AI skills by contributing to an open-source project, gaining hands-on experience and collaborating with other developers.
Show steps
  • Find an open-source AI project that aligns with your interests.
  • Review the project's documentation and contribution guidelines.
  • Identify a bug or feature to work on.
  • Submit your code and participate in code reviews.

Career center

Learners who complete Generative AI, ChatGPT, Copilot & AI Agents Masterclass 2025 will develop knowledge and skills that may be useful to these careers:
Data Visualization Specialist
Data visualization specialists create visual representations of data to help people understand complex information. This role requires both technical skills and an understanding of design principles. One who wants to become a data visualization specialist may find this masterclass useful as it teaches the creation of impactful bar charts, heatmaps, and time-series visualizations. Learning to train and fine-tune custom generative pre-trained transformer models tailored to a company's unique data is also relevant.
See salaries and explore the career path for Data Visualization Specialist
Business Intelligence Analyst
A business intelligence analyst leverages data to identify trends and insights that inform business decisions. This professional translates raw data into actionable strategies. Given this course's focus on Generative AI and tools like ChatGPT and Microsoft Copilot, those in this role may find the skills they need to automate data wrangling, cleaning, and visualization. Further exploration of Z-score analysis and Isolation Forests to detect anomalies is also helpful. Ultimately, this course helps a business intelligence analyst thrive in a data-centric business environment.
See salaries and explore the career path for Business Intelligence Analyst
AI Product Manager
AI product managers oversee the development and launch of AI-powered products. This role requires a blend of technical knowledge, business acumen, and user empathy. This course is designed to unlock the potential of Generative AI and Microsoft Copilot to transform business processes, enhance decision-making, and drive innovation. It may particularly help the AI Product Manager in mastering AI-driven techniques for data wrangling, cleaning, and visualization, using tools to create impactful bar charts, heatmaps, and time-series visualizations.
See salaries and explore the career path for AI Product Manager
Process Automation Specialist
Process automation specialists identify and implement opportunities to automate manual tasks, improving efficiency and reducing errors. This course helps one train and fine-tune custom generative pre-trained transformer models tailored to a company's unique data to automate workflows, generate actionable insights, and optimize operations. This course may be helpful in learning to build AI agents and leveraging CoPilot to streamline complex workflows across platforms like Excel, Word, PowerPoint, and Teams.
See salaries and explore the career path for Process Automation Specialist
Market Research Analyst
Market research analysts study market conditions to examine potential sales of a product or service. They help companies understand what products people want, who will buy them, and at what price. This course helps a market research analyst stay ahead of the curve, mastering AI-driven techniques for data wrangling, cleaning, and visualization, using tools to create impactful bar charts, heatmaps, and time-series visualizations. Furthermore, it helps one explore advanced methods like Z-score analysis and Isolation Forests to detect anomalies and monitor market trends.
See salaries and explore the career path for Market Research Analyst
Strategy Manager
Strategy managers develop and implement long-term strategic plans for organizations. This role typically requires strong analytical and problem-solving skills. This course may be helpful in developing skills in SWOT analysis, financial key performance indicator assessments, and AI-powered tools for supply chain evaluation, marketing strategy optimization, and growth forecasting. Because it is designed to unlock the potential of Generative AI and Microsoft Copilot to transform business processes, enhance decision-making, and drive innovation, it may be useful for success as a strategy manager.
See salaries and explore the career path for Strategy Manager
Management Consultant
Management consultants advise organizations on how to improve their performance and efficiency. This profession often requires a broad understanding of various business functions and the ability to analyze complex problems. This course helps develop skills in SWOT analysis, financial key performance indicator assessments, and AI-powered tools for supply chain evaluation, marketing strategy optimization, and growth forecasting. Using Generative AI and Microsoft Copilot, one may learn to transform business processes, enhance decision-making, and drive innovation to better advise organizations.
See salaries and explore the career path for Management Consultant
Digital Marketing Analyst
Digital marketing analysts measure and analyze the performance of digital marketing campaigns. This course helps digital marketing analysts use AI-powered tools for marketing strategy optimization. The skills taught help one learn to train and fine-tune custom generative pre-trained transformer models tailored to a company's unique data to automate workflows, generate actionable insights, and optimize operations. One may learn to use tools to create impactful bar charts, heatmaps, and time-series visualizations.
See salaries and explore the career path for Digital Marketing Analyst
Data Scientist
Data scientists analyze complex data sets to extract meaningful insights and develop predictive models. This often requires expertise in machine learning and statistical analysis. This course helps build data wrangling skills, using tools to create bar charts, heatmaps, and time-series visualizations. Furthermore, this course explores financial analysis, including extracting insights from 10-K reports, sentiment analysis, and forecasting using sophisticated models. As such, it may be especially useful for a data scientist interested in applying generative AI to finance.
See salaries and explore the career path for Data Scientist
Risk Manager
The risk manager career involves identifying and assessing risks that could impact an organization. Professionals in the field then develop strategies to mitigate these risks. This course may assist risk managers through its exploration of advanced methods like z-score analysis and Isolation Forests to detect anomalies, monitor market trends, and enhance operational efficiency. Through the course, learners will also simulate real-world scenarios to develop robust financial and strategic planning skills.
See salaries and explore the career path for Risk Manager
Business Development Manager
Business development managers identify and pursue new business opportunities. This professional requires a strong understanding of market trends and the ability to build relationships with clients. This course helps equip one with cutting-edge skills to harness AI tools such as ChatGPT, Gemini, Claude, DeepSeek, and Microsoft Copilot for a wide range of business applications. This course's discussion of SWOT analysis, financial key performance indicator assessments, and AI-powered tools for marketing strategy optimization may be helpful in this role.
See salaries and explore the career path for Business Development Manager
Financial Analyst
The financial analyst career involves analyzing financial data, preparing reports, and providing investment recommendations. Skills in forecasting and data visualization are crucial. This course may enhance these skills through its exploration of AI applications for financial analysis, including extracting insights from 10-K reports, sentiment analysis, and forecasting using sophisticated models. Those who want assistance in financial planning and strategic planning may find the simulation of real-world scenarios and assessment of financial key performance indicators useful.
See salaries and explore the career path for Financial Analyst
AI Solutions Architect
AI solutions architects design and oversee the implementation of AI solutions within an organization. This role demands a deep understanding of AI technologies and the ability to translate business requirements into technical specifications. This course's information on training and fine-tuning custom generative pre-trained transformer models tailored to a company's unique data can help one automate workflows, generate actionable insights, and optimize operations. This skill is especially relevant for an AI solutions architect.
See salaries and explore the career path for AI Solutions Architect
Quantitative Analyst
Quantitative analysts use mathematical and statistical methods to solve financial problems. This role typically requires an advanced degree in a quantitative field such as mathematics, statistics, or physics. This course may be useful in the financial analysis techniques it teaches, including extracting insights from 10-K reports, sentiment analysis, and forecasting using sophisticated models. The course helps one simulate real-world scenarios to develop robust financial and strategic planning skills.
See salaries and explore the career path for Quantitative Analyst
Investment Banker
Investment bankers help companies raise capital by issuing stocks and bonds. They also advise on mergers and acquisitions. The financial analysis capabilities taught in this course, including extracting insights from 10-K reports and sentiment analysis, could be directly applicable to the work of an investment banker. Gaining expertise in building AI agents and leveraging CoPilot to streamline complex workflows across platforms like Excel, Word, PowerPoint, and Teams may be helpful in this role as well.
See salaries and explore the career path for Investment Banker

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Generative AI, ChatGPT, Copilot & AI Agents Masterclass 2025.
Cover image
Python for Data Analysis
Save
Comprehensive guide to data analysis with Python, focusing on the Pandas library. It provides a strong foundation for data wrangling, cleaning, and analysis, which are essential skills for leveraging Generative AI in business contexts. This book is particularly useful for Module 3, which covers data wrangling and feature engineering. It is commonly used as a textbook and a reference by data scientists.
Python for Data Analysis
Paperback
Check
Python for Data Analysis
Kindle Edition
Check
Cover image
Competing on Analytics: Updated, with a New...
Save
Explores how organizations can use analytics to gain a competitive advantage. It provides a framework for building an analytical capability and leveraging data-driven insights to improve business performance. This book is more valuable as additional reading to provide a broader context for the course. It is commonly referenced by business leaders and consultants.
Competing on Analytics: Updated, with a New...
Paperback
Check
Competing on Analytics: Updated, with a New...
Kindle Edition
Check

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Course image
Rating
4.6 Filled star Filled star Filled star Filled star Half star
Effort
21 total hours
Via
Udemy
Instructors
Dr. Ryan Ahmed, Ph.D., MBA
Stemplicity Inc.
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Covers a range of AI tools like ChatGPT, Gemini, Claude, and Microsoft Copilot, which are actively used in various industries for automation and insights
Explores AI applications in financial analysis, including extracting insights from 10-K reports and sentiment analysis, which are valuable skills in the finance domain
Includes hands-on projects involving data wrangling, cleaning, and visualization using Pandas, which are essential skills for data-driven decision-making
Introduces machine learning concepts and algorithms like decision trees and random forests, which are fundamental for financial forecasting and predictive modeling
Delves into competitor analysis using Generative AI, covering techniques like vector embeddings, LLM fine-tuning, and RAG, which are useful for strategic business planning
Focuses on specific tools and libraries, so learners should verify that the versions taught are still relevant and supported for their intended applications
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