Data Science & Analytics courses

4.46

This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summ...

4.43

The demand for Data Scientists is immense. In this course, you'll learn how you can play a part in fulfilling this demand and build a long, successful career for yourself. The #1 goal of this...

4.6

Describe what a methodology is and why data scientists need a methodology. Describe the six stages in the Cross Industry Process for Data Mining (CRISP-DM) methodology including Business Understanding and Data Understanding. Describe some of...

3.71

This course explores a variety of machine learning and data science techniques using real life datasets/images/audio collected from several sources. These realistic situations are much better than dummy examples, because they force the student to...

Hypothesis testing lets you ask questions about your datasets and answer them in a statistically rigorous way. In this course you'll learn how and when to use common tests like t-tests, proportion tests, and chi-square...

3.29

This course focuses on one of the main branches of Machine Learning that is Supervised Learning in Python. If you are not familiar with Python, there is nothing to worry about because the Lectures comprising...

Clinical trials are scientific experiments that are conducted to assess whether treatments are effective and safe. They are used by a variety of organizations, including pharmaceutical companies for drug development. Biostatisticians play a key rol...

4.66

BigQuery is Google's fully managed, NoOps, low-cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can...

4.08

"Well done! ! ! ! ! ! I found it the BEST source for me out of many to learn how to implement AI project due the facts it starts from the very basics of...

4.77

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a...

4.58

Build natural language processing systems using TensorFlowProcess text, including tokenization and representing sentences as vectorsApply RNNs, GRUs, and LSTMs in TensorFlowTrain LSTMs on existing text to create original poetry and more

3.33

In this course, we’ll learn about more advanced machine learning methods that are used to tackle problems in the supply chain. We’ll start with an overview of the different ML paradigms (regression/classification) and where the...

4.14

Explain the three basic methods of Econometrics. Apply different econometrics models to examples of daily life. Interpret and carry out several basic analysis strategies (correlation, regression and distribution. Ask relevant questions that can...

4.76

In this course you have the opportunity to use the skills you acquired in the two SAS programming courses to solve realistic problems. This course is also designed to give you a thorough review of...

Missing data is part of any real world data analysis. It can crop up in unexpected places, making analyses challenging to understand. In this course, you will learn how to use tidyverse tools and the...

4.28

Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph...

4.58

Frame a business use case as a machine learning problem. Gain a broad perspective of machine learning and where it can be usedConvert a candidate use case to be driven by machine learningRecognize biases that...

Why Learn Python? Python is a general-purpose, versatile and popular programming language. Python is also a great first language because it is concise and easy to read. A good language to have in any programmer’s...

4.78

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you...

4.42

At the end of the course, you will be able to: *Retrieve data from example database and big data management systems *Describe the connections between data management operations and the big data processing patterns needed...