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Data Analytics Course with Generative AI

Priyanka Mehta

You should have a basic understanding of data analysis, statistics, and familiarity with tools like Excel, SQL, or BI platforms.

By the end of this course, you will be able to:

- Automate Data: Streamline ETL and generate synthetic data using GenAI

- Analyze Insights: Perform EDA and visualize data with AI-powered tools

- Predict Outcomes: Build models and simulate risk for better decisions

- Apply GenAI: Use GenAI across real-world analytics with measurable impact

Ideal for analysts, data professionals, and business leaders advancing data strategy with AI.

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What's inside

Syllabus

Exploration to Visualization

Explore how Generative AI is transforming the data analytics process from integration to visualization. Learn the types of analytics such as descriptive, diagnostic, predictive, and prescriptive, and GenAI's role in each stage. Automate ETL processes, enhance data quality, and generate synthetic datasets using tools like ChatGPT-4 and MOSTLY AI. Perform EDA and create insights with tools like Julius AI and Tableau Pulse.

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Career center

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

Data Analyst

A Data Analyst collects, processes, and performs statistical analyses on data to translate numbers into plain language insights. This professional often works to identify trends, create reports, and support decision-making across an organization. The Data Analytics Course with Generative AI is exceptionally well-suited for anyone pursuing a career as a Data Analyst. It covers mastering the four types of analytics—descriptive, diagnostic, predictive, and prescriptive—and shows how Generative AI enhances each stage. The course directly teaches automation of ETL processes, performance of Exploratory Data Analysis, and visualization with AI-powered tools like Julius AI and Tableau Pulse, which are daily tasks for a data analyst. Furthermore, learning to build predictive models and apply Generative AI in practical business scenarios empowers analysts to deliver deeper, more impactful insights and drive data-driven strategies within any organization.

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Data Scientist

A Data Scientist uncovers insights and builds sophisticated models to solve complex business problems. This role involves everything from data collection and cleaning to developing algorithms for prediction and classification. The Data Analytics Course with Generative AI directly addresses core responsibilities for a Data Scientist like building predictive models, forecasting trends, and conducting risk analysis through real-world simulations. It also provides expertise in automating ETL processes and generating synthetic data using Generative AI tools like ChatGPT-4 and MOSTLY AI, crucial for efficient data preparation and robust model training. Mastering how Generative AI enhances descriptive, diagnostic, predictive, and prescriptive analytics will be particularly beneficial for developing innovative solutions and delivering measurable impact in this advanced field.

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Machine Learning Engineer

A Machine Learning Engineer designs, builds, and deploys algorithms and systems that learn from data to make predictions or decisions. This critical role involves translating data science prototypes into production-ready solutions and ensuring their efficient operation. The Data Analytics Course with Generative AI provides a robust foundation for an aspiring Machine Learning Engineer, specifically by focusing on building predictive models, forecasting trends, and understanding performance metrics. The course's emphasis on Generative AI for data modeling, scenario simulation, and automating ETL processes directly contributes to the practical skills needed to develop and optimize machine learning pipelines. Furthermore, applying Generative AI in real-world analytics prepares you for the challenges of integrating advanced AI capabilities into scalable, impactful systems.

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Analytics Engineer

An Analytics Engineer designs, builds, and optimizes the data infrastructure that powers analytics and reporting. This role focuses on making data reliable, accessible, and useful for data scientists and business analysts. The Data Analytics Course with Generative AI is highly relevant for an Analytics Engineer, particularly in its focus on automating ETL processes and enhancing data quality using Generative AI. The course delves into optimizing ETL, which is a fundamental responsibility, and generating synthetic data with tools like ChatGPT-4. Understanding how Generative AI transforms data analytics from integration to visualization provides a comprehensive perspective on building robust data pipelines. Furthermore, exploring Generative AI's role in data modeling and scenario simulation directly aids in structuring data for advanced analytical applications and predictive outcomes.

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Business Intelligence Analyst

A Business Intelligence Analyst transforms raw data into understandable and actionable insights that guide strategic business decisions. This involves creating dashboards, reports, and visualizations to monitor performance and identify trends. The Data Analytics Course with Generative AI provides crucial skills for a Business Intelligence Analyst, especially in performing Exploratory Data Analysis and visualizing data with AI-powered tools like Julius AI and Tableau Pulse. Learning to master descriptive and diagnostic analytics, enhanced by Generative AI, directly supports the core function of understanding past and present business data. The ability to automate ETL processes also streamlines data preparation, allowing for more efficient and accurate reporting and deeper insights into business operations.

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Consultant Data Strategy

A Consultant Data Strategy advises organizations on how to effectively collect, manage, analyze, and leverage their data to achieve business objectives. This role involves designing comprehensive data roadmaps and implementing analytical solutions. The Data Analytics Course with Generative AI is highly beneficial for a Consultant Data Strategy, equipping them with a deep understanding of how Generative AI is transforming the entire data analytics process from integration to visualization. Mastering the four types of analytics and Generative AI's role in each stage provides a strategic framework for advising clients. The ability to demonstrate automation of ETL processes, generate synthetic data, and apply Generative AI in practical business scenarios with measurable impact helps in articulating advanced data strategies and guiding their successful implementation throughout an enterprise.

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Risk Analyst

A Risk Analyst identifies, assesses, and mitigates potential financial and operational risks that an organization faces. This role involves analyzing data to foresee potential problems and recommend strategies to minimize adverse impacts. The Data Analytics Course with Generative AI directly addresses key aspects of a Risk Analyst's responsibilities, particularly through its emphasis on conducting risk analysis through real-world simulations. The course trains learners to build predictive models and forecast trends, which are essential for proactive risk identification and assessment. Furthermore, understanding how Generative AI can be applied across real-world analytics, including scenario simulation, provides powerful tools for assessing complex risk landscapes and developing robust mitigation strategies to protect organizational assets.

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Financial Modeler

A Financial Modeler creates quantitative models to forecast financial performance, assess investment opportunities, and support strategic decision-making. These models are crucial for business planning, valuation, and risk assessment. The Data Analytics Course with Generative AI offers skills that are relevant for a Financial Modeler, particularly its focus on building predictive models, forecasting trends, and conducting risk analysis through real-world simulations. The course's exploration of Generative AI's role in data modeling and scenario simulation provides advanced techniques for creating more dynamic and robust financial forecasts. Understanding how to apply Generative AI across real-world analytics helps in developing sophisticated models that can adapt to changing market conditions and provide deeper insights for better financial decisions and strategic planning.

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Product Manager Artificial Intelligence

A Product Manager Artificial Intelligence defines the strategy, roadmap, and features for AI-powered products. This role requires a deep understanding of AI technologies and their potential to solve user problems and create business value. The Data Analytics Course with Generative AI provides valuable insights for an aspiring Product Manager Artificial Intelligence by demonstrating how Generative AI can be applied across real-world analytics with measurable impact. Understanding how Generative AI enhances descriptive, diagnostic, predictive, and prescriptive analytics offers a strategic view of AI's capabilities. The course's focus on building predictive models, forecasting trends, and addressing integration challenges helps in conceptualizing and guiding the development of effective AI applications, bridging the gap between technical potential and market needs.

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Marketing Analyst

A Marketing Analyst collects and analyzes data on market trends, customer behavior, and campaign performance to optimize marketing strategies and drive business growth. The insights derived help shape future marketing initiatives and improve return on investment. The Data Analytics Course with Generative AI may be useful for a Marketing Analyst by providing skills to analyze insights and visualize data with AI-powered tools like Tableau Pulse and Julius AI, directly aiding in understanding campaign effectiveness. Learning to master descriptive, diagnostic, predictive, and prescriptive analytics allows for a comprehensive understanding of marketing data, from past performance to future trends. The ability to build predictive models and apply Generative AI in practical business scenarios can significantly enhance targeted marketing efforts and personalize customer experiences based on data-driven forecasts.

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Operations Research Analyst

An Operations Research Analyst uses advanced analytical methods like mathematical modeling, optimization, and simulation to help organizations make more efficient decisions and solve complex operational problems. The Data Analytics Course with Generative AI may be useful for an Operations Research Analyst, particularly through its emphasis on building predictive models, forecasting trends, and conducting risk analysis through real-world simulations. The course's exploration of Generative AI's role in data modeling and scenario simulation directly aligns with the techniques used to optimize systems and processes. Understanding performance metrics and applying Generative AI in practical business scenarios can enhance the development of more sophisticated optimization models and improve decision-making, though many roles in this field typically require an advanced degree.

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Quantitative Analyst

A Quantitative Analyst applies mathematical and statistical methods to financial and risk management problems, often developing complex models for pricing, trading, and risk assessment. The Data Analytics Course with Generative AI may be useful for a Quantitative Analyst, especially through its focus on building predictive models, forecasting trends, and conducting risk analysis through real-world simulations. The course's exploration of Generative AI's role in data modeling and scenario simulation provides relevant skills for developing sophisticated analytical frameworks. Understanding performance metrics and applying Generative AI in practical business scenarios can inform the development of more robust and efficient quantitative models, though many roles in this field typically require an advanced degree like a master's or PhD.

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Data Quality Analyst

A Data Quality Analyst ensures the accuracy, completeness, and consistency of data across an organization's systems. This role is crucial for maintaining reliable information that supports robust decision-making and analytics. The Data Analytics Course with Generative AI may be helpful for a Data Quality Analyst, particularly through its focus on automating ETL processes and enhancing data quality using Generative AI. The course explicitly covers optimizing ETL, which includes managing and improving data integrity from ingestion to analysis. Learning to generate synthetic datasets using tools like ChatGPT-4 and MOSTLY AI can also aid in testing and validating data quality processes without compromising real data. Understanding how Generative AI transforms data handling can lead to more innovative and efficient data quality management strategies.

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Customer Relationship Management Analyst

A Customer Relationship Management Analyst focuses on analyzing customer data to understand behavior, predict needs, and improve customer satisfaction and retention. This role uses data to personalize interactions and enhance customer journeys. The Data Analytics Course with Generative AI may be useful for a Customer Relationship Management Analyst by equipping them with skills to analyze insights and visualize data with AI-powered tools. Learning to master descriptive, diagnostic, predictive, and prescriptive analytics allows for a comprehensive understanding of customer lifecycles and preferences. The ability to build predictive models and apply Generative AI in practical business scenarios can significantly enhance customer segmentation, predict churn, and personalize marketing efforts, leading to more effective customer engagement strategies and improved business outcomes.

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Business Systems Analyst

A Business Systems Analyst works at the intersection of business and technology, identifying organizational needs and designing information systems solutions to meet them. This role requires understanding processes, data flows, and system capabilities. The Data Analytics Course with Generative AI may be helpful for a Business Systems Analyst by providing a strong understanding of how Generative AI can optimize data workflows, automate analysis, and generate actionable insights. Understanding the four types of analytics—descriptive, diagnostic, predictive, and prescriptive—and Generative AI's role in each stage helps in identifying opportunities for system improvements. The course's focus on automating ETL processes and applying Generative AI in practical business scenarios equips analysts to recommend and design more efficient and intelligent business systems that leverage modern analytical capabilities.

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