Mastering Generative AI for Data Analytics from edX

Currently 82% of global companies are either using or exploring the use of AI in their organization (Website: Exploding Topics),. Generative AI skills are now essential career skills.

Stay current by unlocking the power of generative AI in data analytics, using cutting-edge models and tools for deeper insights. Designed for both aspiring and experienced data analysts, this course requires basic familiarity with data analytics, prompt engineering, Python, and generative AI. You'll explore core concepts, industry applications, and ethical considerations while mastering techniques like prompting, visualization, storytelling, and querying.

Through hands-on labs, you'll gain practical experience with leading generative AI tools including ChatGPT, ChatCSV, Mostly.AI, and SQLthroughAI. Evaluate your knowledge using practice quizzes and prove your knowledge to others by passing the graded assessments. You'll apply your knowledge in a real-world, shareable data analytics project that you can share with prospective employers. Upon completion of this course, share your verified course certificate with your professional connections and prospective employers.

Enroll today to transform data into actionable insights using generative AI.

What's inside

Learning objectives

Describe the use of generative ai tools and techniques for data analytics across industries
Implement generative ai for data analytic processes including data preparation, analysis, visualization, and storytelling

Evaluate real-world case studies that successfully apply generative ai to derive meaningful insights
Analyze ethical challenges associated with using generative ai for data analytics

Describe the use of generative ai tools and techniques for data analytics across industries
Implement generative ai for data analytic processes including data preparation, analysis, visualization, and storytelling
Evaluate real-world case studies that successfully apply generative ai to derive meaningful insights
Analyze ethical challenges associated with using generative ai for data analytics

Syllabus

Module 0: Welcome

Video: Course Introduction

General Information

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Teaches prompt engineering, visualization, storytelling, and querying, which are essential skills for data analysts looking to leverage generative AI

Requires basic familiarity with data analytics, prompt engineering, Python, and generative AI, suggesting a need for foundational knowledge before starting

Includes hands-on labs using tools like ChatGPT, ChatCSV, Mostly.AI, and SQLthroughAI, offering practical experience with leading generative AI technologies

Presented by IBM, a company recognized for its work in data analytics and artificial intelligence solutions for businesses and organizations

Examines ethical challenges associated with using generative AI for data analytics, which is an important consideration for responsible AI implementation

Covers the use of Microsoft Copilot, which may be subject to updates and changes that render some course content obsolete over time

Reviews summary

Practical genai for data analytics

According to learners, this course offers a largely positive experience for those looking to apply generative AI in data analytics. Students particularly praise the hands-on labs and the practical final project, which many found instrumental in applying concepts and building a portfolio. The course covers a range of useful tools and includes a valuable module on ethical considerations. However, some reviewers noted that a solid understanding of the stated prerequisites (Python, basic AI) is crucial, as the course moves quickly.

Organized content in logical modules.

"The course is broken down into logical, easy-to-digest modules."

"I liked the structure with videos, readings, and labs in each section."

"The progression from basics to more complex applications felt natural."

Introduces various relevant GenAI tools.

"Exploring different tools like ChatCSV and Mostly.AI was a highlight."

"The course gave me a good overview of several generative AI tools applicable to data analytics tasks."

"It's helpful that they show demos using multiple platforms, not just one."

Valuable coverage of ethical considerations.

"The module on ethical considerations for using GenAI was particularly insightful and relevant."

"It was good to see the course address the ethical implications alongside the technical skills."

"I found the section on responsible AI for data professionals very important."

Strong practical focus through labs and project.

"The hands-on coding and projects are the strongest part of the course for me."

"I really benefited from the labs using tools like ChatGPT and SQLthroughAI."

"The final project provided a great opportunity to apply everything learned and is perfect for my portfolio."

"I appreciate the emphasis on practical application through the labs provided in each module."

Requires a strong background as outlined.

"Learners should definitely have a solid foundation in Python and data analytics before starting."

"I struggled a bit with the pace, realizing my Python skills weren't as strong as needed."

"Make sure you are comfortable with the prerequisites; the course doesn't waste time on basics."

"While the course is great, I felt the assumed prior knowledge was a bit high for some parts."

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 Mastering Generative AI for Data Analytics with these activities:

Review Python Fundamentals

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Reinforce your understanding of Python fundamentals, which are essential for using generative AI tools and libraries in data analytics.

Browse courses on Python Programming

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Review basic Python syntax and data structures.
Practice writing simple Python scripts.
Familiarize yourself with data manipulation libraries like Pandas.

Brush up on Prompt Engineering

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Improve your prompt engineering skills to effectively interact with generative AI models for data analysis tasks.

Browse courses on Prompt Design

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Study prompt engineering techniques for different generative AI models.
Experiment with various prompts to generate desired outputs.
Analyze the impact of prompt variations on the quality of generated content.

Read 'Generative AI with Python and TensorFlow 2'

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Gain a deeper understanding of generative AI models by studying a book that covers their implementation using Python and TensorFlow.

View Generative AI with Python and TensorFlow 2:... on Amazon

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Read the book chapter by chapter.
Implement the examples provided in the book.
Experiment with different parameters and architectures.

Four other activities

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Practice SQL Query Generation with AI

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Enhance your ability to use generative AI for querying databases by practicing with different datasets and scenarios.

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Use generative AI tools to generate SQL queries from natural language descriptions.
Test the generated queries against various databases.
Refine your prompts to improve the accuracy of the generated queries.

Create a Data Visualization Dashboard using Generative AI

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Solidify your understanding of generative AI for data visualization by creating a dashboard that showcases insights generated from a dataset.

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Select a dataset relevant to your interests.
Use generative AI tools to generate visualizations from the data.
Assemble the visualizations into an interactive dashboard.
Write a short summary of the insights revealed by the dashboard.

Develop a Generative AI-Powered Data Augmentation Tool

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Apply your knowledge of generative AI to create a tool that augments datasets for improved data analysis.

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Choose a dataset and identify areas for augmentation.
Implement generative AI techniques to create synthetic data.
Evaluate the impact of the augmented data on data analysis tasks.
Document your tool and share it with the community.

Read 'Deep Learning with Python'

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Expand your understanding of the deep learning foundations behind generative AI by studying a comprehensive guide.

View Deep Learning with R on Amazon

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Read the relevant chapters on deep learning architectures.
Implement the examples provided in the book.
Relate the concepts to generative AI models.

Career center

Learners who complete Mastering Generative AI for Data Analytics will develop knowledge and skills that may be useful to these careers:

Data Analyst

A data analyst examines and interprets data to identify trends and insights. This role uses statistical techniques, data visualization, and reporting tools to provide actionable recommendations to organizations. A course like Mastering Generative AI for Data Analytics can greatly enhance a data analyst's skills by introducing cutting-edge generative AI models and tools. The course helps data analysts to streamline data preparation, perform complex analyses, and create compelling visualizations, all amplified by AI. With hands-on experience using generative AI tools, data analysts can discover new ways to derive insights from data, and deliver more impactful results to stakeholders. The course provides a real world project that will be a great addition to any data analyst's portfolio. The course also provides a verified certificate that can be shared with prospective employers.

See salaries and explore the career path for Data Analyst

Data Visualization Specialist

A data visualization specialist focuses on creating compelling and informative visual representations of data. This role requires expertise in data visualization tools and techniques, as well as a strong understanding of design principles and storytelling. A data visualization specialist can benefit from the Mastering Generative AI for Data Analytics course by learning how to leverage generative AI to create more effective and engaging visualizations. The course's emphasis on generative AI tools can help data visualization specialists automate the creation of charts, graphs, and dashboards, allowing them to focus on the more creative aspects of their work. This role benefits from the storytelling section of the course.

See salaries and explore the career path for Data Visualization Specialist

Business Intelligence Analyst

A business intelligence analyst focuses on analyzing data to provide insights that support strategic decision-making within an organization. This role involves creating dashboards, reports, and data visualizations to communicate findings to stakeholders. This Mastering Generative AI for Data Analytics course may be useful for a business intelligence analyst by providing them with the skills to leverage AI in data preparation, analysis, and insight generation. The course's emphasis on generative AI tools such as ChatGPT, ChatCSV, and SQLthroughAI helps business intelligence analysts to automate tasks, uncover new patterns in data, and create more effective visualizations. Business intelligence analysts can use these skills to provide more timely and actionable insights, improving the overall effectiveness of their organization's decision-making processes. The course provides a verified certificate that can be shared with prospective employers.

See salaries and explore the career path for Business Intelligence Analyst

Healthcare Data Analyst

A healthcare data analyst specializes in analyzing healthcare data to improve patient outcomes, reduce costs, and enhance operational efficiency. This role requires a strong understanding of healthcare data standards, as well as expertise in data analysis and reporting. The Mastering Generative AI for Data Analytics course can enhance a healthcare data analyst's ability to derive meaningful insights from complex healthcare datasets. The course's focus on generative AI can help automate data preparation, create compelling visualizations, and generate data-driven stories that inform healthcare decision-making. The course also provides relevant case studies.

See salaries and explore the career path for Healthcare Data Analyst

Market Research Analyst

A market research analyst studies market conditions, consumer behavior, and competitor activities to provide insights that inform marketing strategies and product development. This role involves collecting and analyzing data from various sources, as well as creating reports and presentations to communicate findings. Market research analysts can use the Mastering Generative AI for Data Analytics course to enhance their data analysis skills and uncover new patterns and insights. The course focus on generative AI helps automate data preparation, create compelling visualizations, and generate data driven stories that inform marketing strategies. This may be particularly useful for analyzing large datasets from social media platforms or customer surveys.

See salaries and explore the career path for Market Research Analyst

Data Scientist

A data scientist uses advanced analytical techniques and machine learning algorithms to extract knowledge and insights from data. This role often involves developing predictive models, conducting experiments, and communicating findings to technical and non-technical audiences. A data scientist can benefit from a course like Mastering Generative AI for Data Analytics as it provides hands-on experience with leveraging generative AI tools for data preparation, analysis, and visualization. The course's focus on models like ChatGPT and Mostly.AI helps data scientists to explore new approaches to data analysis, automate repetitive tasks, and discover innovative solutions to complex problems. Data scientists that take this course will also gain valuable experience in the ethical considerations associated with AI.

See salaries and explore the career path for Data Scientist

Analytics Manager

An analytics manager leads a team of analysts and oversees the development of analytical solutions to support business decision-making. This role involves setting priorities, allocating resources, and ensuring the quality and relevance of analytical outputs. Mastering Generative AI for Data Analytics may be useful for an analytics manager by providing them with the knowledge and skills to leverage generative AI in their team's workflows. The course provides insights into how generative AI tools can be used for data preparation, analysis, visualization, and storytelling. An analytics manager can apply this knowledge to drive innovation within their team, improve the efficiency of analytical processes, and deliver more impactful insights to stakeholders.

See salaries and explore the career path for Analytics Manager

Machine Learning Engineer

A machine learning engineer designs, develops, and deploys machine learning models and systems. This role requires a strong understanding of algorithms, programming, and data engineering. As a machine learning engineer, the Mastering Generative AI for Data Analytics course can enhance your ability to integrate generative AI into data analytics workflows. The course may be useful by providing practical experience with tools like ChatGPT, ChatCSV, and SQLthroughAI. A machine learning engineer can leverage these skills to build more efficient and effective data processing pipelines and create innovative applications of generative AI in data analysis. This role typically requires an advanced degree.

See salaries and explore the career path for Machine Learning Engineer

Supply Chain Analyst

A supply chain analyst focuses on optimizing the flow of goods, information, and finances across the supply chain. This role involves analyzing data related to inventory levels, transportation costs, and supplier performance to identify areas for improvement. Supply chain analysts can benefit from a course like Mastering Generative AI for Data Analytics by learning how to leverage AI to enhance their data analysis and decision-making capabilities. The course's emphasis on generative AI tools helps automate data preparation, create compelling visualizations, and generate data driven stories that inform supply chain strategies. By mastering these skills, supply chain analysts can drive efficiency, reduce costs, and improve customer satisfaction.

See salaries and explore the career path for Supply Chain Analyst

Data Engineer

A data engineer builds and maintains the infrastructure that supports data storage, processing, and analysis. This role requires expertise in database systems, data warehousing, and ETL processes. A data engineer benefits from the Mastering Generative AI for Data Analytics course by exploring how generative AI can streamline data preparation, querying, and integration tasks. The course's hands-on labs with tools like ChatGPT, ChatCSV, and SQLthroughAI provide data engineers with practical experience in leveraging AI to automate and optimize their data pipelines. The course also has a focus on data generation and augmentation.

See salaries and explore the career path for Data Engineer

AI Consultant

An AI consultant advises organizations on how to integrate artificial intelligence technologies to improve their business processes and outcomes. This role requires a deep understanding of AI capabilities, industry trends, and business strategy. The concepts covered in the Mastering Generative AI for Data Analytics course may be useful for an AI consultant. The course helps to demonstrate the practical applications of generative AI in data-driven decision-making. By mastering the tools and techniques taught in the course, an AI consultant can better guide clients on how to leverage AI to enhance their data analytics capabilities and achieve their business goals. The AI consultant may, for example, recommend how their clients can use AI to perform storytelling with generated code.

See salaries and explore the career path for AI Consultant

Statistician

A statistician applies statistical methods to collect, analyze, and interpret data to solve problems and inform decision-making. This role requires a deep understanding of statistical theory, as well as expertise in statistical software and data analysis techniques. A statistician can use the Mastering Generative AI for Data Analytics course to enhance their ability to derive deeper insights from data and communicate their findings more effectively. The course's focus on generative AI for data analysis and visualization can help statisticians uncover new patterns and trends in complex datasets. This role typically requires an advanced degree.

See salaries and explore the career path for Statistician

Risk Analyst

A risk analyst identifies and assesses potential risks that could impact an organization's financial stability, operations, or reputation. This role requires a strong understanding of risk management principles, as well as expertise in data analysis and modeling. The Mastering Generative AI for Data Analytics course may be useful for a risk analyst by providing them with the skills to leverage AI in data analysis and visualization. The course may be useful as it helps risk analysts automate data preparation, create compelling visualizations, and generate actionable insights for risk mitigation. By mastering these skills, risk analysts can better identify, assess, and manage risks across their organizations.

See salaries and explore the career path for Risk Analyst

Financial Analyst

A financial analyst analyzes financial data, prepares reports, and provides recommendations to support investment decisions and financial planning. This role requires a strong understanding of finance principles, as well as expertise in financial modeling and data analysis. Mastering Generative AI for Data Analytics may be useful to a financial analyst by providing them with the skills to leverage AI in data analysis and visualization. The course may be useful as it helps financial analysts automate data preparation, create compelling visualizations, and generate actionable insights for investment decisions. The financial analyst may also use the AI to generate data-driven stories.

See salaries and explore the career path for Financial Analyst

Database Administrator

A database administrator is responsible for the performance, integrity, and security of an organization's databases. This role involves designing, implementing, and maintaining database systems, as well as ensuring that data is accessible and secure. The Mastering Generative AI for Data Analytics course may be useful to a database administrator, by providing insights into how generative AI can be used to streamline data querying and management tasks. The course's hands-on labs with tools like SQLthroughAI can help database administrators automate data retrieval and manipulation, improving the efficiency of their work. This may also result in higher quality data.

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Mastering Generative AI for Data Analytics

What's inside

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Reviews summary

Practical genai for data analytics

Activities

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