Regression is a machine learning technique that can be used to model and predict the relationship between variables, features and a continuous numerical target. In this course, learners will identify use cases for simple linear regression, focusing on the relationship between two variables only. Students will build, evaluate, and interpret a simple linear regression model in Python, with an emphasis on checking the model for explanatory and predictive power.

Regression is a machine learning technique that can be used to model and predict the relationship between variables, features and a continuous numerical target. In this course, learners will identify use cases for simple linear regression, focusing on the relationship between two variables only. Students will build, evaluate, and interpret a simple linear regression model in R, with an emphasis on checking the model for explanatory and predictive power.

A 4-hour course for intermediate-level data scientists / engineers that covers Spark architecture and fundamentals including RDDs, DataFrames, Datasets.

A 6-hour course for intermediate-level data scientists / engineers that covers spark partitions, benchmarking, performance optimization and monitoring.

This course is designed for learners who would like to learn about statistics and apply it for decision-making. This course is a comprehensive review of advanced statistics topics on probability like permutations and combinations, joint probability, conditional probability, marginal probability, and Bayes` theorem that provides a way to revise existing predictions or update probabilities given new or additional evidence.

This course is designed for learners who would like to learn about statistics and apply it for decision-making. This course is a comprehensive review of advanced statistics topics on probability distributions like binomial, mulitnomial, hypergeometric, poisson, exponential and uniform distributions enabling us to obtain estimates of the probability that a certain event may occur, or estimate the variability of occurrence.

Once students know how to build data visualizations, they can incorporate data storytelling best practices to maximize the impact of their reports and discoveries. This course covers effective techniques to map out a data presentation and practice those skills in Tableau. By the end of the program, students will be able to establish context around data, identify appropriate charts for their messaging, and communicate findings clearly to stakeholders.

This course covers the basics of Support Vector machine algorithm. It helps students implement and optimize the model for a dataset.

This course describes Test-driven development (TDD) as a software development process that follows a short, repeating cycle of turning requirements into test cases, then improving the code to pass the tests.

An introduction to CI/CD and how to perform testing using automated CI/CD pipelines using CircleCI.

An introduction to software testing and types of testing using Python.

This practical, hands-on course dives into testing of an entire ML pipeline starting from data and model validation and ending with the integration tests of the pipeline as a whole.

An introduction to software testing and types of testing using Node.js.

From individual hobbyists to the largest corporations, just about everyone agrees that it’s important to test your code. But which testing framework should you use? In the Python world, “pytest” has rocketed to popularity in the last few years — largely because of how easy it is to use and integrate into your software-testing framework and workflow.

This course intermediate concepts in natural language processing, equipping learners with the ability to clean and process large amounts of text data, segregating text into different groups and topics, as well as finding similarities between different documents.

This course intermediate concepts in natural language processing, equipping learners with the ability to clean and process large amounts of text data, segregating text into different groups and topics, as well as finding similarities between different documents. As natural language can be vague and subjective, the course also presents ways to evaluate and interpret these language models.

A course that builds foundational knowledge of what an operating system is. It walks through the different core concepts of OS and its inner workings.

A course that builds foundational knowledge of what an operating system in Python. It walks through the different core concepts of OS and its inner workings.

Jest is a tool for testing React applications. This course will teach you basic and intermediate Jest testing techniques, including running tests, snapshot testing, testing React components, and module mocking.

A course that introduces unit testing and how it can be performed using Pytest in Python.