In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
Mining Quality Prediction Using Machine & Deep Learning
In this 1.5-hour long project-based course, you will be able to:
- Understand the theory and intuition behind Simple and Multiple Linear Regression.
- Import Key python libraries, datasets and perform data visualization
- Perform exploratory data analysis and standardize the training and testing data.
- Train and Evaluate different regression models using Sci-kit Learn library.
- Build and train an Artificial Neural Network to perform regression.
- Understand the difference between various regression models KPIs such as MSE, RMSE, MAE, R2, and adjusted R2.
- Assess the performance of regression models and visualize the performance of the best model using various KPIs.
Ready to master the fundamentals that keep businesses compliant and employees paid correctly? This Short Course was created to help accounting professionals accomplish essential payroll processing mastery.
By completing this course, you'll be able to confidently distinguish mandatory federal withholdings, systematically process employee time data, and implement verification procedures that prevent costly payroll errors you can apply immediately in your workplace.
By the end of this course, you will be able to:
Recognize mandatory federal payroll withholdings.
Apply payroll data entry procedures to process employee time and verify calculations.
This course is unique because it combines federal tax compliance knowledge with hands-on system practice using real-world scenarios that mirror daily accounting operations.
To be successful in this project, you should have a background in basic accounting principles and familiarity with business software applications.
In this course, you’ll learn how to create Tableau dashboards that connect data to decision-making. Starting with stakeholder planning and data requirements, you’ll define goals, success metrics, and key questions. Then, you’ll clean and prepare a real-world tech salary dataset using Tableau’s filtering, aliasing, and data type tools. You’ll turn these insights into impactful dashboards using calculated fields, grouping, and interactivity. Finally, you’ll explore how to interpret and present dashboards effectively through Socratic dialogue—critiquing design choices, analyzing KPIs, and refining your data story. By the end, you’ll be able to deliver dashboards that are insightful, persuasive, and tailored to audience needs.
Valuation and Financial Analysis For Startups Capstone
This is a peer review course. In the capstone project, you are going to apply what you have learned in the previous courses. The final output from this project is an estimation of a firm. You can choose either a public company or a startup depending on the availability of information on the firm. If you have your own startup, then you can do this capstone project on the startup. If not, then you can do this project of a public company. Therefore, the first step is selecting an actual company that you are interested in. Next, you have to do the research on and describe the firm’s industry and business. Based on your research, you make an estimate of firm’s growth, cash flows and earnings. In order to do this, you need to apply what you have learned in financial statement analysis. Once you find firm’s cash flows and earnings, you can apply what you have learned in discounted cash flow method and multiple methods to find the value of the company. In addition to the valuation, you will be given a hypothetical project and have to decide whether to take the project if the opportunity is given to the company of your choice. Be doing this Capstone project, you will complete your understanding of valuation and financial analysis of startups.
Dell Technologies Establishing Your Sales Strategy
This course is designed to enhance your sales skills and deepen your understanding of IT concepts. This course will teach you to identify and demonstrate effective strategies for qualifying opportunities, ensuring you can recognize and pursue the most promising leads. You will learn the sequence and significance of each stage of the sales process, enabling you to navigate sales cycles with confidence.
Understanding buyer types and motivations is crucial, and you will craft probing questions tailored to each buyer type. You will develop a mindset for building trust, learning the factors that contribute to credibility and the consequences of lacking it.
Building rapport is essential, and you will identify the five key areas for establishing strong connections with customers. You will also learn strategies for delivering compelling insights to the right contacts within customer organizations.
Finally, you will gain knowledge of key technologies and understand ways to leverage this knowledge to find solutions for your customers.
This course is designed for anyone with an interest in a career in IT sales. No previous experience is necessary.
By the end of this course, you will be able to:
Use knowledge of buyer types and motivations to craft probing questions appropriate for each buyer type.
Describe the sequence and significance of each stage of the sales process.
Identify and demonstrate effective strategies for qualifying opportunities.
Identify strategies for conveying insights to the right contact within the customer organization in a compelling manner.
Identify the five key areas for establishing rapport.
Identify the factors that are key for establishing credibility & trust with customers.
Describe the relationship between software and external hardware in the functioning of an enterprise solutions.
Describe key data center technologies.
Recall the various types of questions they can ask, the value of each type and the natural order of asking.
Discuss, define, and practice probing and drill-down questioning to uncover further important customer information.
Why are markets commonly believed to be the best way of allocating resources and organizing economic activity? This course will answer this critical question while examining its implications for pricing, market entry and exit, short-term and long-term business strategies, and the forecasting of key market variables. The course introduces fundamental topics in the economic analysis of markets, and some of the analytical tools used to study them, as a means to build an economic intuition and fostering an understanding of a variety of market conditions and market forces.
After taking this course, you will be able to:
- Explain the basics of supply and demand curves.
- Characterize variable and fixed costs.
- Identify short-run and long-run market exit prices.
- Construct short-run and long-run supply curves.
- Construct demand curves.
- Identify short-run and long-run equilibria in competitive markets.
- Predict short-run and long-run market prices.
- Interpret a market price path.
- Explain firm entry, exit, and profitability in competitive markets.
Software requirements: None
Strong visuals aren’t just cosmetic—they’re critical for attracting clicks, growing your audience, and reinforcing your brand on YouTube. In this course, you’ll learn how to design effective thumbnails, banners, and channel icons. Discover the psychology behind high-performing thumbnails, how to stay within YouTube’s technical specifications, and how to build visual consistency across your channel. You’ll walk away with professional-looking assets that make a strong first impression and boost viewer engagement.
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.
This course is the first in a sequence of three. It describes the two basic PGM representations: Bayesian Networks, which rely on a directed graph; and Markov networks, which use an undirected graph. The course discusses both the theoretical properties of these representations as well as their use in practice. The (highly recommended) honors track contains several hands-on assignments on how to represent some real-world problems. The course also presents some important extensions beyond the basic PGM representation, which allow more complex models to be encoded compactly.
Figma UI UX Design Essentials Pt.3: Prototypes & Handoff
In Part 3 of the Figma UI UX Design Essentials series, with Daniel Scott as your instructor, you’ll bring your designs to life through interactive prototypes and learn how to prepare your work for seamless developer handoff. This course focuses on building real-world UX workflows—teaching you how to create engaging animations, smart transitions, and micro interactions that elevate your user experience.
You’ll also learn how to share and collaborate with stakeholders, developers, and clients, using Figma’s built-in tools for comments, version history, and developer inspection. Dan walks you through advanced techniques like interactive components, flow mapping, and using Figma for responsive design—all in an easy-to-follow, project-driven format.
By the end of this course, you’ll not only be able to build high-fidelity prototypes, but you’ll also understand how to hand off your work professionally. Whether you're preparing for a UX design role or building your freelance portfolio, this final installment will help you move from a capable designer to a confident, job-ready pro.
Instructor bio:
Daniel Walter Scott is a digital designer, Adobe Certified Instructor, and founder of Bring Your Own Laptop (BYOL). With over 14 years of teaching experience, he has helped thousands of learners worldwide master design and creative software across print, web, video, and now 3D. Daniel is an Adobe Certified Expert and Adobe Certified Instructor who combines industry expertise with a teaching style that’s practical, engaging, and memorable.
Originally from New Zealand, Daniel has lived and taught across Australia, Ireland, and beyond—sharing his skills with a truly global creative community. He’s passionate about helping students build real-world skills they can carry into their careers and creative projects.
When he’s not teaching, Daniel enjoys life with his Irish wife and kids. He brings this personal, down-to-earth perspective into his courses, making complex tools feel approachable and fun to learn.
Getting Started with Neo4J Enterprise on Google Cloud
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will load data from a Google Cloud Storage Bucket to Neo4j then explore the data using the Neo4J browser and Cypher query language
Python for Data Visualization:Matplotlib & Seaborn(Enhanced)
In this hands-on project, we will understand the fundamentals of data visualization with Python and leverage the power of two important python libraries known as Matplotlib and seaborn. We will learn how to generate line plots, scatterplots, histograms, distribution plot, 3D plots, pie charts, pair plots, countplots and many more!
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
