Our Courses

Cell Biology: The Cytoskeleton and Cell Cycle

Cell Biology: The Cytoskeleton and Cell Cycle

How do we know what we know about cells? Enhance your scientific thinking and data analysis skills with this in-depth adventure through cell biology.

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Cell Biology: Transport and Signaling

Cell Biology: Transport and Signaling

How do we know what we know about cells? Enhance your scientific thinking and data analysis skills with this in-depth adventure through cell biology.

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Data Analysis with Tidyverse

Data Analysis with Tidyverse

This course continues our gentle introduction to programming in R designed for 3 types of learners. It will be right for you, if: • you want to do data analysis but don’t know programming • you know programming but aren’t too familiar with R • you know some R programming but want to learn more about the tidyverse verbs It is best taken following the first course in the specialization or if you already are familiar with ggplot, RMarkdown, and basic function writing in R.

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  • 17 hours
  • English
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Quantitative Methods for Biology

Quantitative Methods for Biology

Learn introductory programming and data analysis in MATLAB, with applications to biology and medicine.

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Causal Diagrams: Draw Your Assumptions Before Your Conclusions

Causal Diagrams: Draw Your Assumptions Before Your Conclusions

Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal inference.

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  • 9
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High-Dimensional Data Analysis

High-Dimensional Data Analysis

A focus on several techniques that are widely used in the analysis of high-dimensional data.

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Data Science: Inference and Modeling

Data Science: Inference and Modeling

Learn inference and modeling, two of the most widely used statistical tools in data analysis.

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Data Science Math Skills

Data Science Math Skills

Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time.

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  • 13 hours
  • English
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IBM Data Analytics with Excel and R

IBM Data Analytics with Excel and R

Prepare for the in-demand field of data analytics. In this program, you’ll learn high valued skills like Excel, Cognos Analytics, and R programming language to get job-ready in less than 3 months. Data analytics is a strategy-based science where data is analyzed to find trends, answer questions, shape business processes, and aid decision-making. This Professional Certificate focuses on data analysis using Microsoft Excel and R programming language.

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Total Data Quality

Total Data Quality

This specialization aims to explore the Total Data Quality framework in depth and provide learners with more information about the detailed evaluation of total data quality that needs to happen prior to data analysis. The goal is for learners to incorporate evaluations of data quality into their process as a critical component for all projects.

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Build Data Analysis tools using R and DPLYR

Build Data Analysis tools using R and DPLYR

In this 2-hour long project-based course, you will learn one of the most powerful data analysis tools of the experts: the DPLYR package.

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  • 3 hours
  • English
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Sustainability Analyst Fundamentals

Sustainability Analyst Fundamentals

The ASU Sustainability specialization introduces the role of a sustainability analyst, assesses sustainability challenges that face the planet and employers, and equips learners with the foundational skills needed to address these challenges.

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Precalculus through Data and Modelling

Precalculus through Data and Modelling

This specialization helps to build the foundational material to use mathematics as a tool to model, understand, and interpret the world around us. This is done through studying functions, their properties, and applications to data analysis. Concepts of precalculus provide the set of tools for the learner to begin their scientific career, preparing them for future science and calculus courses. This specialization is designed for all learners, not just those interested in further mathematics courses.

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From Data to Insights with Google Cloud

From Data to Insights with Google Cloud

Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets.

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Meta Marketing Analytics

Meta Marketing Analytics

This eight-course program is designed for anyone looking to gain in-demand technical skills to kickstart a career as a marketing analyst or better analyze their business. No experience necessary. Developed by marketing analytics experts at Aptly and Meta, and designed to prepare you for jobs that include Marketing Analyst, Marketing Researcher, and more. You’ll learn basic marketing principles, how data informs marketing decisions, and how you can apply the OSEMN data analysis framework to approach common analytics questions.

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Design of Experiments

Design of Experiments

Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software.

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Player  Evaluation, Team Performance and Roster Management

Player Evaluation, Team Performance and Roster Management

This course will provide students with an introduction to using specific data techniques to address key sports administrative functions in team and roster management. The primary focus is on the use of data analysis in player acquisition and retention, as well as player and coach assessment. Students will learn how the collective bargaining agreement (CBA) and standard player contract (SPC) provide the framework for management decisions in which data analysis play a pivotal role. There is a focus on data science techniques as applied to sports datasets.

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  • 16 hours
  • English
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Programming for Data Science

Programming for Data Science

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems.

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Data Analysis and Visualization with Power BI

Data Analysis and Visualization 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 will learn report design and formatting in Power BI, which offers extraordinary visuals for building reports and dashboards. Additionally, you will learn how to use report navigation to tell a compelling, data-driven story in Power BI.

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  • 30 hours
  • English
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Statistics with Python

Statistics with Python

This specialization is designed to teach learners beginning and intermediate concepts of statistical analysis using the Python programming language. Learners will learn where data come from, what types of data can be collected, study data design, data management, and how to effectively carry out data exploration and visualization. They will be able to utilize data for estimation and assessing theories, construct confidence intervals, interpret inferential results, and apply more advanced statistical modeling procedures.

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Data Analysis and Interpretation

Data Analysis and Interpretation

Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions. The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights.

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Pre MBA Quantitative Skills

Pre MBA Quantitative Skills

This Specialization is designed to equip you with a basic understanding of business finance, accounting, and data analysis. We've put together these three courses with the explicit intent of helping people prepare for th…

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Data Understanding and Visualization

Data Understanding and Visualization

The "Data Understanding and Visualization" course provides students with essential statistical concepts to comprehend and analyze datasets effectively. Participants will learn about central tendency, variation, location, correlation, and other fundamental statistical measures. Additionally, the course introduces data visualization techniques using Pandas, Matplotlib, and Seaborn packages, enabling students to present data visually with appropriate plots for accurate and efficient communication. Learning Objectives: 1.

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Accounting Data Analytics

Accounting Data Analytics

This specialization develops learners’ analytics mindset and knowledge of data analytics tools and techniques. Specifically, this specialization develops learners' analytics skills by first introducing an analytic mindset, data preparation, visualization, and analysis using Excel. Next, this specialization develops learners' skills of using Python for data preparation, data visualization, data analysis, and data interpretation and the ability to apply these skills to issues relevant to accounting.

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Mathematical Methods for Data Analysis

Mathematical Methods for Data Analysis

Learn mathematical methods for data analysis including mathematical formulations and computational methods. Some well-known machine learning algorithms such as k-means are introduced in the examples.

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