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Our Courses
Big Data Analysis Deep Dive
The job market for architects, engineers, and analytics professionals with Big Data expertise continues to increase. The Academy’s Big Data Career path focuses on the fundamental tools and techniques needed to pursue a career in Big Data. This course includes: data processing with python, writing and reading SQL queries, transmitting data with MaxCompute, analyzing data with Quick BI, using Hive, Hadoop, and spark on E-MapReduce, and how to visualize data with data dashboards.
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Course by
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Self Paced
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14 hours
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English
Statistics for Data Science with Python
This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis.
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Course by
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Self Paced
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14 hours
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English
Fundamentals of Machine Learning for Supply Chain
This course will teach you how to leverage the power of Python to understand complicated supply chain datasets. Even if you are not familiar with supply chain fundamentals, the rich data sets that we will use as a canvas will help orient you with several Pythonic tools and best practices for exploratory data analysis (EDA). As such, though all datasets are geared towards supply chain minded professionals, the lessons are easily generalizable to other use cases.
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Course by
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Self Paced
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13 hours
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English
Surveillance Systems: Analysis, Dissemination, and Special Systems
In this course, we'll build on the previous lessons in this specialization to focus on some very specific skills related to public health surveillance. We'll learn how to get the most out of surveillance data analysis, focusing specifically on interpreting time trend data to detect temporal aberrations as well as person, place, and time in the context of surveillance data. We'll also explore strategies for the presentation of surveillance data and some of the complex legal elements that affect its use.
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Course by
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Self Paced
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6 hours
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English
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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Course by
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Self Paced
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3 hours
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English
Crime Zone Heatmaps with Python and Folium
In this one hour long project-based course, you will tackle a real-world problem in data analysis and visualization.
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Course by
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Self Paced
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3 hours
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English
Sort and Filter Data in SQL using MySQL Workbench
In this project you will use MySQL Workbench to write SQL queries that retrieve, sort, and filter data from tables in a relational database. Adding filtering to a query ensures that only the data needed is displayed in the query result. Sorting is applied to arrange the rows in that query result into an order that is meaningful to the data’s user. Adding code to an SQL query to filter and sort data generates a query result that makes data analysis easier for users, enabling more effective decision-making. Note: This course works best for learners who are based in the North America region.
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Course by
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Self Paced
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3 hours
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English
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 regressio
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Course by
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Self Paced
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2 hours
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English
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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Course by
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Self Paced
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English
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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Course by
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Self Paced
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13 hours
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English
Data Analyst Career Guide and Interview Preparation
Data analytics professionals are in high demand around the world, and the trend shows no sign of slowing. There are lots of great jobs available, but lots of great candidates too. How can you get the edge in such a competitive field? This course will prepare you to enter the job market as a great candidate for a data analyst position. It provides practical techniques for creating essential job-seeking materials such as a resume and a portfolio, as well as auxiliary tools like a cover letter and an elevator pitch.
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Course by
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Self Paced
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11 hours
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English
Use Power Bi for Financial Data Analysis
In this project, learners will have a guided look through Power Bi dynamic reports and visualizations for financial data analysis.
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Course by
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Self Paced
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3 hours
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English
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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Course by
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Self Paced
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English
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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Course by
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Self Paced
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English
Introduction to Data Science
Interested in learning more about data science, but don’t know where to start? This 4-course Specialization from IBM will provide you with the key foundational skills any data scientist needs to prepare you for a career in data science or further advanced learning in the field. This Specialization will introduce you to what data science is and what data scientists do. You’ll discover the applicability of data science across fields, and learn how data analysis can help you make data driven decisions.
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Course by
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English
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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Course by
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Self Paced
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English
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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Course by
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Self Paced
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English
Matrix Methods
Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction. Optional examples using Python are used to illustrate the concepts and allow the learner to experiment with the algorithms.
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Course by
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Self Paced
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7 hours
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English
Data Analysis and Visualization Foundations
Deriving insights from data and communicating findings has become an increasingly important part of virtually every profession. This Specialization prepares you for this data-driven transformation by teaching you the core principles of data analysis and visualization and by giving you the tools and hands-on practice to communicate the results of your data discoveries effectively. You will be introduced to the modern data ecosystem. You will learn the skills required to successfully start data analysis tasks by becoming familiar with spreadsheets like Excel.
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Course by
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Self Paced
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English
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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Course by
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Self Paced
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English
Analyze Data in a Model Car Database with MySQL Workbench
In this project, you’ll perform exploratory data analysis for Mint Classics Company, a retailer of model cars. The company is looking to close one of its storage facilities. Your objective is to recommend inventory reduction strategies that won’t negatively impact customer service. Using MySQL Workbench, you’ll familiarize yourself with the sample database, run SQL queries to identify factors affecting storage space and propose inventory reduction approaches.
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Course by
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Self Paced
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3 hours
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English
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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Course by
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Self Paced
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English
Data Analytics in the Public Sector with R
Every government entity collects and stores millions of data points to perform administrative and legislative duties, allocate resources, and make decisions. Professionals in the public sector need the necessary skills to accurately interpret and inform administrators and policymakers about the meaning behind these data. This Specialization will equip you with fundamental technical skills using the R programming language to gather, manipulate, analyze, visualize, and interpret data to inform public policy and public administrative functions.
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Course by
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Self Paced
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English
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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Course by
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Self Paced
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English
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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Course by
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Self Paced
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17 hours
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English