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Our Courses
Python Programming Fundamentals
This introductory course is designed for beginners and individuals with limited programming experience who want to embark on their software development or data science journey using Python. Throughout the course, learners will gain a solid understanding of algorithmic thinking, Python syntax, code testing, debugging techniques, and modular code development--essential skills for a successful career in software engineering, development, or data science.
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Course by
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Self Paced
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24 hours
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English
Data Analysis and Visualization
By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python). Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time.
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Course by
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Self Paced
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11 hours
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English
An Introduction to Programming using Python
Maximise your employability, by learning the basics of coding in Python. Python is a versatile programming language used for developing websites and software, task automation, data analysis and more. In this course, you'll embark on an exciting journey into the world of Python and gain valuable skills that will enable you to start thinking about a career in programming. Through exercises and practical projects, you will gain confidence and deepen your understanding of coding in Python.
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Course by
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Self Paced
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9 hours
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English
Data Analysis in R: Predictive Analysis with Regression
Increasingly, predictive analytics is shaping companies' decisions about limited resources. In this project, you will build a regression model to make predictions. We will start this hands-on project by exploring the dataset and creating visualizations for the dataset. By the end of this 2-hour-long project, you will be able to build and interpret the result of a simple linear regression model in R. Also, you will learn how to perform model assessments and check for assumptions using diagnostic plots.
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Course by
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Self Paced
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3 hours
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English
Perform basic data analysis tasks using Java streams
In this 1-hour long project-based course, you will learn how to create a Java Stream object based on an array of data, and understand the distinction between terminal and intermediate stream operations. You will iterate through the data stream using the forEach method, and use a range of Stream methods to perform logical operations on the data stream. You will perform basic statistical calculations on a stream of numeric data, and string operations on a stream of string data. You will learn how to use the map, filter, and reduce Stream methods.
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Course by
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Self Paced
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3 hours
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English
Measuring Total Data Quality
By the end of this second course in the Total Data Quality Specialization, learners will be able to: 1. Learn various metrics for evaluating Total Data Quality (TDQ) at each stage of the TDQ framework. 2. Create a quality concept map that tracks relevant aspects of TDQ from a particular application or data source. 3. Think through relative trade-offs between quality aspects, relative costs and practical constraints imposed by a particular project or study. 4. Identify relevant software and related tools for computing the various metrics. 5.
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Course by
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Self Paced
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9 hours
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English
Survey Data Collection and Analytics Project (Capstone)
The Capstone Project offers qualified learners to the opportunity to apply their knowledge by analyzing and comparing multiple data sources on the same topic. Students will develop a research question, access and analyze relevant data, and critically examine the quality of each data source.
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Course by
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Self Paced
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14 hours
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English
Predict Career Longevity for NBA Rookies using Scikit-learn
By the end of this project, you will be able to apply data analysis to predict career longevity for NBA Rookie using python.
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Course by
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Self Paced
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3 hours
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English
Data Visualization with R
In this course, you will learn the Grammar of Graphics, a system for describing and building graphs, and how the ggplot2 data visualization package for R applies this concept to basic bar charts, histograms, pie charts, scatter plots, line plots, and box plots. You will also learn how to further customize your charts and plots using themes and other techniques. You will then learn how to use another data visualization package for R called Leaflet to create map plots, a unique way to plot data based on geolocation data.
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Course by
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Self Paced
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12 hours
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English
Data Analysis Using Pyspark
One of the important topics that every data analyst should be familiar with is the distributed data processing technologies. As a data analyst, you should be able to apply different queries to your dataset to extract useful information out of it. but what if your data is so big that working with it on your local machine is not easy to be done. That is when the distributed data processing and Spark Technology will become handy.
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Course by
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Self Paced
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3 hours
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English
Harnessing the Power of Data with Power BI
This course forms part of the Microsoft Power BI Analyst Professional Certificate. This Professional Certificate consists of a series of courses that offers a good starting point for a career in data analysis using Microsoft Power BI. In this course, you’ll learn about the role of a data analyst and the main stages involved in the data analysis process with a focus on applying them using Microsoft Power BI.
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Course by
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Self Paced
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16 hours
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English
Mathematical Biostatistics Boot Camp 2
Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.
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Course by
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Self Paced
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12 hours
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English
Go Beyond the Numbers: Translate Data into Insights
This is the third of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll learn how to find the story within data and tell that story in a compelling way. You'll discover how data professionals use storytelling to better understand their data and communicate key insights to teammates and stakeholders. You'll also practice exploratory data analysis and learn how to create effective data visualizations.
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Course by
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Self Paced
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33 hours
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English
Hierarchical relational data analysis using python
By the end of this project you will learn how to analyze Hierarchical Data.
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Course by
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Self Paced
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2 hours
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English
Google Sheets - Advanced Topics
This course builds on some of the concepts covered in the earlier Google Sheets course. In this course, you will learn how to apply and customize themes In Google Sheets, and explore conditional formatting options. You will learn about some of Google Sheets’ advanced formulas and functions. You will explore how to create formulas using functions, and you will also learn how to reference and validate your data in a Google Sheet. Spreadsheets can hold millions of numbers, formulas, and text. Making sense of all of that data can be difficult without a summary or visualization.
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Course by
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Self Paced
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3 hours
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English
SQL for Data Science Capstone Project
Data science is a dynamic and growing career field that demands knowledge and skills-based in SQL to be successful. This course is designed to provide you with a solid foundation in applying SQL skills to analyze data and solve real business problems. Whether you have successfully completed the other courses in the Learn SQL Basics for Data Science Specialization or are taking just this course, this project is your chance to apply the knowledge and skills you have acquired to practice important SQL querying and solve problems with data.
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Course by
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Self Paced
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35 hours
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English
Big Data Analysis with Scala and Spark (Scala 2 version)
Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout.
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Course by
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Self Paced
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28 hours
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English
Empathy, Data, and Risk
Risk Management and Innovation develops your ability to conduct empathy-driven and data-driven analysis in the domain of risk management. This course introduces empathy as a professional competency. It explains the psychological processes that inhibit empathy-building and the processes that determine how organizational stakeholders respond to risk. The course guides you through techniques to gather risk information by understanding a stakeholder’s thoughts, feelings, and goals. These techniques include interviewing, brainstorming, and empathy mapping.
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Course by
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Self Paced
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13 hours
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English
Mastering Data Analysis with Pandas: Learning Path Part 4
In this structured series of hands-on guided projects, we will master the fundamentals of data analysis and manipulation with Pandas and Python. Pandas is a super powerful, fast, flexible and easy to use open-source data analysis and manipulation tool. This guided project is the fourth of a series of multiple guided projects (learning path) that is designed for anyone who wants to master data analysis with pandas. 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.
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Course by
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Self Paced
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3 hours
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English
Machine Learning with PySpark: Data Analysis using SQL
This Guided Project is for beginning Python Developers.
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Course by
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Self Paced
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3 hours
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English
Build Data Analysis and Transformation Skills in R using DPLYR
Congratulations you've made it to Part 2 of the DPLYR series! In a moment you will be taken to Rhyme where a Virtual Machine with R, R Studio and DPLYR awaits.
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Course by
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Self Paced
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2 hours
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English
Introduction to Data Analytics on Google Cloud
In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started.
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Course by
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Self Paced
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4 hours
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English
Build and deploy a stroke prediction model using R
In this project, you’ll help a leading healthcare organization build a model to predict the likelihood of a patient suffering a stroke. The model could help improve a patient’s outcomes.
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Course by
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Self Paced
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3 hours
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English
Advanced Business Analytics Capstone
The analytics process is a collection of interrelated activities that lead to better decisions and to a higher business performance. The capstone of this specialization is designed with the goal of allowing you to experience this process. The capstone project will take you from data to analysis and models, and ultimately to presentation of insights. In this capstone project, you will analyze the data on financial loans to help with the investment decisions of an investment company.
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Course by
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Self Paced
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20 hours
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English
R Tutorial
This comprehensive course is your one-stop-shop for learning the R programming language, a popular tool for data analysis, visualization, and statistical computing. Our course covers all the fundamentals of R, including data types, control structures, functions, and packages. Throughout the course, you'll explore how to import, manipulate, and visualize data using R. Plus, you'll learn how to perform statistical analyses and create custom graphics. By the end of this course, you'll have a solid foundation in R programming and be able to use it for a wide range of data analysis tasks.
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Course by
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Self Paced
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12 hours
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English