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Applied AI in Data Analytics

via Coursera Specialization

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Provider

Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

8 weeks, 5 hours a week
Sessions

Self-Paced
Level

Beginner

Found in

Overview

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This Specialization is designed for learners who want to use AI to analyze data, uncover insights, and support data-informed decision-making. Through three courses, you’ll build foundational AI knowledge, develop effective prompt engineering skills, and learn how to apply AI to practical data analytics tasks and workflows. By the end of the Specialization, you’ll be prepared to use AI tools to work more efficiently with data, identify meaningful patterns and insights, and communicate findings to support business decisions.

Syllabus

Course 1: Practical AI Foundations
Course 2: Practical Prompt Engineering with AI
Course 3: AI-Enabled Data Analytics

Courses

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Practical AI Foundations introduces learners to the practical use of artificial intelligence in everyday work, helping them build confidence using AI tools to communicate more effectively, increase productivity, and streamline routine tasks. Designed for professionals across industries, students, and anyone looking to improve workplace efficiency, this course focuses on applying AI responsibly to solve real-world challenges. Learners explore how to interact with AI tools such as ChatGPT and Google Assistant, write effective prompts, improve written communication, automate everyday tasks, organize information, and enhance productivity. Through hands-on practice and real-world scenarios, learners develop practical skills they can immediately apply in professional and personal settings while gaining an understanding of responsible AI use. Rather than focusing on how AI is built, the course emphasizes how AI can be used effectively as a workplace assistant to support better decision-making, communication, and organization. By the end of the course, learners will be prepared to confidently incorporate AI into their daily workflows and use it as a practical tool to work more efficiently.
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Practical Prompt Engineering with AI teaches learners how to communicate effectively with generative AI to produce more accurate, useful, and efficient results. Through hands-on practice, learners develop prompting techniques for summarizing information, refining AI responses, conducting research, analyzing data, generating visualizations, and creating AI-generated images. Throughout the course, learners explore a variety of prompting strategies, including extractive and abstractive summarization, iterative prompt refinement, and structured prompting. They also gain experience using specialized AI tools—including Claude, predefined Custom GPTs, and DALL·E—to complete workplace tasks more effectively. Practical activities demonstrate how AI can support research, data analysis, content creation, image interpretation, and visual communication. By the end of the course, learners will confidently create effective prompts, choose the right AI tools for different scenarios, and apply practical AI techniques to improve productivity, communication, and decision-making in everyday work.
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AI-Enabled Data Analytics prepares learners to use artificial intelligence to analyze data, uncover insights, and make more informed business decisions. Designed for business professionals, aspiring analysts, managers, and anyone interested in improving their analytical skills, the course explores how AI-powered tools can simplify data analysis, automate repetitive tasks, and support data-driven decision-making. Learners develop practical skills in organizing, analyzing, and interpreting data while using AI to streamline common analytics workflows. Through hands-on activities and real-world business scenarios, they learn how to identify trends, generate meaningful insights, create visualizations, and communicate findings effectively. The course also explores responsible AI use, helping learners understand both the opportunities and limitations of AI-assisted analytics. Rather than focusing on programming or building AI models, the curriculum emphasizes practical workplace application. By the end of the course, learners will be prepared to confidently use AI-enabled data analytics tools to improve productivity, support strategic decision-making, and solve real-world business challenges.