Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
Our Courses
Data Science Fundamentals
This specialization demystifies data science and familiarizes learners with key data science skills, techniques, and concepts. The course begins with foundational concepts such as analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, and then moves on to compare data science with classical statistical techniques.
-
Course by
-
Self Paced
-
English
Mastering Data Analysis with Pandas: Learning Path Part 2
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 second 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.
-
Course by
-
Self Paced
-
3 hours
-
English
Wrangling Data in the Tidyverse
Data never arrive in the condition that you need them in order to do effective data analysis. Data need to be re-shaped, re-arranged, and re-formatted, so that they can be visualized or be inputted into a machine learning algorithm. This course addresses the problem of wrangling your data so that you can bring them under control and analyze them effectively.
-
Course by
-
Self Paced
-
14 hours
-
English
IBM Data Analyst
Prepare for a career in the high-growth field of data analytics. In this program, you’ll learn in-demand skills like Python, Excel, and SQL to get job-ready in as little as 4 months. Data analysis is the process of collecting, storing, modeling, and analyzing data that can inform executive decision-making, and the demand for skilled data analysts has never been greater. This program will teach you the foundational data skills employers are seeking for entry-level data analytics roles.
-
Course by
-
Self Paced
-
English
Healthcare Data Models
Career prospects are bright for those qualified to work in healthcare data analytics. Perhaps you work in data analytics, but are considering a move into healthcare where your work can improve people’s quality of life.
-
Course by
-
Self Paced
-
12 hours
-
English
Data Processing and Manipulation
The "Data Processing and Manipulation" course provides students with a comprehensive understanding of various data processing and manipulation concepts and tools. Participants will learn how to handle missing values, detect outliers, perform sampling and dimension reduction, apply scaling and discretization techniques, and explore data cube and pivot table operations. This course equips students with essential skills for efficiently preparing and transforming data for analysis and decision-making. Learning Objectives: 1.
-
Course by
-
Self Paced
-
29 hours
-
English
Excel Skills for Data Analytics and Visualization
As data becomes the modern currency, so the ability to quickly and accurately analyse data has become of paramount importance. Therefore, data analytics and visualization are two of the most sought after skills for high paying jobs with strong future growth prospects. According to an IBM report, the Excel tools for data analytics and visualization are among the top 10 competencies projected to show double-digit growth in their demand.
-
Course by
-
Self Paced
-
English
BigQuery Soccer Data Analytical Insight
This is a self-paced lab that takes place in the Google Cloud console. Learn how to create deeper analytical insights from soccer event data using BigQuery. BigQuery can be used to perform more sophisticated data analysis. In this lab, you will analyze soccer event data to achieve real insight from the dataset.
-
Course by
-
Self Paced
-
1 hour
-
English
Data Science Methods for Quality Improvement
Data analysis skills are widely sought by employers, both nationally and internationally. This specialization is ideal for anyone interested in data analysis for improving quality and processes in business and industry. The skills taught in this specialization have been used extensively to improve business performance, quality, and reliability. By completing this specialization, you will improve your ability to analyze data and interpret results as well as gain new skills, such as using RStudio and RMarkdown.
-
Course by
-
Self Paced
-
English
Bayesian Statistics: Capstone Project
This is the capstone project for UC Santa Cruz's Bayesian Statistics Specialization. It is an opportunity for you to demonstrate a wide range of skills and knowledge in Bayesian statistics and to apply what you know to real-world data. You will review essential concepts in Bayesian statistics with lecture videos and quizzes, and you will perform a complex data analysis and compose a report on your methods and results.
-
Course by
-
12 hours
-
English
Deep Learning and Reinforcement Learning
This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. First you will learn about the theory behind Neural Networks, which are the basis of Deep Learning, as well as several modern architectures of Deep Learning.
-
Course by
-
32 hours
-
English
Applied Data Science
This action-packed Specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. If you’re interested in pursuing a career in data science, and already have foundational skills or have completed the Introduction to Data Science Specialization, this program is for you! This 4-course Specialization will give you the tools you need to analyze data and make data driven business decisions leveraging computer science and statistical analysis.
-
Course by
-
Self Paced
-
English
The Data Driven Manager
In the Data Driven Manager specialization, you will learn how to first understand the type of data that you have (or want to generate), then describe it with numbers and graphs to communicate with your audience. You will practice using probability and distributions to understand the underlying nature of your data to make decisions and solve problems in a way that increases the likelihood of a desired outcome. You will learn the steps to create a plan to answer business and engineering questions and reduce risk when making decisions.
-
Course by
-
Self Paced
-
English
Precalculus: Mathematical Modeling
This course 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 beginning student to begin their scientific career, preparing them for future science and calculus courses. This course is designed for all students, not just those interested in further mathematics courses.
-
Course by
-
Self Paced
-
10 hours
-
English
Learn SQL Basics for Data Science
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, Delta Lake and more.
-
Course by
-
Self Paced
-
English
Machine Learning: Algorithms in the Real World
This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application. After completing all four courses, you will have gone through the entire process of building a machine learning project.
-
Course by
-
Self Paced
-
English
Data Science and Analysis Tools - from Jupyter to R Markdown
This specialization is intended for people without programming experience who seek an approachable introduction to data science that uses Python and R to describe and visualize data sets. This course will equip learners with foundational knowledge of data analysis suitable for any analyst roles. In these four courses, you will cover everything from data wrangling to data visualization.
-
Course by
-
Self Paced
-
English
Market Research
The Market Research Specialisation focuses on the essentials of research and the research process.
-
Course by
-
Self Paced
-
English
Exploratory Data Analysis for the Public Sector with ggplot
Learn about the core pillars of the public sector and the core functions of public administration through statistical Exploratory Data Analysis (EDA). Learn analytical and technical skills using the R programming language to explore, visualize, and present data, with a focus on equity and the administrative functions of planning and reporting. Technical skills in this course will focus on the ggplot2 library of the tidyverse, and include developing bar, line, and scatter charts, generating trend lines, and understanding histograms, kernel density estimations, violin plots, and ridgeplots.
-
Course by
-
Self Paced
-
18 hours
-
English
Health Data Science Foundation
This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios. We cover deep learning (DL) methods, healthcare data and applications using DL methods.
-
Course by
-
Self Paced
-
24 hours
-
English
Data Analysis in Python: Using Pandas DataFrames
This Guided Project Data Analysis in Python: Using Pandas DataFrames is for those who are interested in using python for data science in practice. In this 90-minute Guided Project, learn how to import and visualize an IMDb data set in Pandas. You will learn how to import JSON data into a Pandas Dataframe and apply the data preparation process to ensure the data is ready for analysis. To achieve this, we will explore the famous IMDb Movies dataset. We will start with importing our JSON data into a Pandas data frame.
-
Course by
-
Self Paced
-
2 hours
-
English
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.
-
Course by
-
Self Paced
-
24 hours
-
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.
-
Course by
-
Self Paced
-
11 hours
-
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.
-
Course by
-
Self Paced
-
9 hours
-
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.
-
Course by
-
Self Paced
-
3 hours
-
English