Harvard University · edX
Data Science: Building Machine Learning Models
4.4133 ratingsBuild a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.
Overview
In this course, you’ll learn to communicate insights in ways that drive real decisions. You’ll explore how to choose the right format to present your findings and tailor your message to technical and non-technical audiences.
You’ll start by learning how to craft data stories that provide context and align with business goals. Then, you’ll apply those skills by designing clear, effective charts that highlight a single insight. Next, you’ll build interactive dashboards in Tableau using features like annotations, tooltips, and “Show Me.” These skills transfer easily to tools like Power BI and Looker Studio. In the final module, you’ll prepare for the job search: analyzing roles, tailoring your resume and portfolio, building your network, and getting ready for interviews.
Throughout the course, you’ll practice applying these skills to realistic business scenarios so you’re ready to share insights that influence decisions.
Syllabus 4
- Data storytelling fundamentals 3.5 hours
This module explores the art and strategy of data storytelling, an essential skill for communicating insights effectively in business and technical contexts. You'll learn how data storytelling differs from traditional reporting by focusing on narrative, context, and audience engagement. Through han…
- Creating charts with Tableau 5 hours
This module introduces the principles of effective data visualization and reporting using Tableau. You’ll begin by creating a Tableau Public account and building your first workbook. Then, through guided practice and scenario-based exercises, you’ll learn to choose the right type of insight and vis…
- Creating dashboards & stories with Tableau 3.5 hours
In this module, you'll build a strong foundation in data visualization and dashboard creation, with a focus on using Tableau effectively. You’ll start by exploring key features of Tableau and other common visualization tools, then move on to best practices in dashboard design and delivery formats s…
- The Job Search 3.5 hours
This module guides you through the key stages of the job search process, from identifying opportunities to succeeding in interviews. You'll learn to interpret job listings, distinguish between hard and soft requirements, and apply strategies for finding roles that align with your skills. You'll exp…
Advantages and disadvantages
Advantages
- Structured courses with graded quizzes, assignments and deadlines you can reset.
- A shareable certificate from the university or company when you pay.
- Financial aid is often approved for students in India (apply 15 days before you need it).
- Andrew Ng and his team are among the clearest AI teachers anywhere.
- Short courses are made with the companies building the tools (OpenAI, Google, AWS, Hugging Face).
- From DeepLearning.AI, a well-regarded name.
- Self-paced: start any time.
- A clear syllabus (4 parts) you can see before you start.
Disadvantages
- Paid after a 7-day free trial (Coursera Plus or per course).
- Some courses can be audited for free, but graded work and certificates need payment.
- Short courses are 1–2 hours: an introduction, not mastery.
- Some notebooks need a paid Pro plan or your own API key.
Some points apply to every course of this kind; see how we rank.
This course is paid. Here is how to take it for free
- Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
- Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.
Taught by
- Sean BarnesData Science Leader at Netflix
DeepLearning.AI is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (90/100). Andrew Ng's courses.
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