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Our Courses
Data Engineering Capstone Project
Showcase your skills in this Data Engineering project! In this course you will apply a variety of data engineering skills and techniques you have learned as part of the previous courses in the IBM Data Engineering Professional Certificate. You will demonstrate your knowledge of Data Engineering by assuming the role of a Junior Data Engineer who has recently joined an organization and be presented with a real-world use case that requires architecting and implementing a data analytics platform. In this Capstone project you will complete numerous hands-on labs.
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Course by
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13 hours
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English
Deep Learning for Real Estate Price Prediction
In this hands-on guided project, we will predict real estate prices with deep learning. In this project, we will predict home sale prices in King County in the U.S. between May, 2014 and May, 2015 using several features such as number of bedrooms, bathrooms, view, and square footage. This guided project is practical and directly applicable to the real estate industry. You can add this project to your portfolio of projects which is essential for your next job interview.
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Self Paced
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2 hours
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English
PredictionX: Lost Without Longitude
Explore the history of navigation, from stars to satellites.
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Self Paced
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60
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English
PredictionX: Omens, Oracles & Prophecies
This course is an overview of divination systems, ranging from ancient Chinese bone burning to modern astrology.
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Course by
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Self Paced
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English
Physical and Advanced Side-Channel Attacks
Software-based and physical side-channel attacks have similar techniques. But physical attacks can observe properties and side effects that are usually not visible on the software layer. Thus, they are often considered the most dangerous side-channel attacks. In this course, we learn both about physical side-channel attacks but also about more advanced software-based side channels using prefetching and branch prediction. You will work with these attacks and understand how to mitigate them.
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Course by
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Self Paced
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English
Introduction to Astrophysics
Learn about the physical phenomena at play in astronomical objects and link theoretical predictions to observations.
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Course by
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Self Paced
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18
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English
Predictive Analytics: Basic Modeling Techniques
What is Predictive Analytics? These methods lie behind the most transformative technologies of the last decade, that go under the more general name Artificial Intelligence or AI. In this course, the focus is on the skills that will allow you to fit a model to data, and measure how well it performs. We will be doing enough data science so that you get hands-on familiarity with understanding a dataset, fitting a model to it, and generating predictions.
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Course by
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26
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English
COVID-19 mRNA Vaccine Degradation Prediction
In this 2-hour long project-based course, you will learn how to predict mRNA Vaccine Degradation Rates at various positions of the molecule.
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Course by
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Self Paced
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2 hours
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English
Employee Attrition Prediction Using Machine Learning
In this project-based course, we will build, train and test a machine learning model to predict employee attrition using features such as employee job satisfaction, distance from work, compensation and performance. We will explore two machine learning algorithms, namely: (1) logistic regression classifier model and (2) Extreme Gradient Boosted Trees (XG-Boost). This project could be effectively applied in any Human Resources department to predict which employees are more likely to quit based on their features.
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Course by
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3 hours
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English
Practical Decision-Making Using No-code ML on AWS
In this course, you will discover how to solve business problems with machine learning, no coding required. You will explore Amazon SageMaker Canvas, a visual point-and-click interface that allows you to generate accurate ML predictions without requiring any machine learning experience or having to write a single line of code. At the end of the course, you will walk away understanding how to make better business decisions using no-code machine learning.
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Course by
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Self Paced
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5 hours
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English
Compare time series predictions of COVID-19 deaths
By the end of this project, you will learn how to perform the entire time series analysis workflow for the daily COVID-19 deaths.
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Course by
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Self Paced
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2 hours
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English
Analysis of Algorithms
This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. In addition, this course covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings. All the features of this course are available for free.
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Course by
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Self Paced
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21 hours
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English
The Sun and the Total Eclipse of August 2017
A total eclipse is one of the most spectacular sights you can ever see! It looks like the end of the world may be at hand. There is a black hole in the sky where the sun should be. Pink flames of solar prominences and long silver streamers of the sun's corona stretch across the sky. It gets cold, and animals do strange things. People scream and shout and cheer, and remember the experience their whole life. But total eclipses are important scientifically as well. They let us see parts of the sun’s atmosphere that are otherwise invisible.
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Course by
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Self Paced
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8 hours
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English
Data Science Coding Challenge: Loan Default Prediction
In this coding challenge, you'll compete with other learners to achieve the highest prediction accuracy on a machine learning problem. You'll use Python and a Jupyter Notebook to work with a real-world dataset and build a prediction or classification model. Important Information: How to register? To participate, you’ll need to complete simple steps. First, click the “Start Project” button to register. Next, you’ll need to create a Coursera Skills Profile, which only takes a few minutes.
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Course by
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Self Paced
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3 hours
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English
PredictionX: John Snow and the Cholera Epidemic of 1854
An in-depth look at the 1854 London cholera epidemic in Soho and its importance for the field of epidemiology.
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Course by
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Self Paced
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English
XG-Boost 101: Used Cars Price Prediction
In this hands-on project, we will train 3 Machine Learning algorithms namely Multiple Linear Regression, Random Forest Regression, and XG-Boost to predict used cars prices.
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Course by
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Self Paced
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3 hours
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English
Build and deploy a stroke prediction model using R
In this project, you’ll help a leading healthcare organization build a model to predict the likelihood of a patient suffering a stroke. The model could help improve a patient’s outcomes.
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Course by
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Self Paced
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3 hours
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English
Renewable Energy Futures
Renewable energy's future is bright, yet uncertain. Will it continue to grow rapidly? Is current growth sufficient to achieve climate stabilization? How do related technologies, like electric vehicles and heat pumps, fit in? This course will shed light on the many confusing and at-times inconsistent claims and predictions for renewable energy. We’ll review promising new renewable technologies and approaches, such as floating platforms for wind turbines and building-integrated photovoltaics (PV), and point out key opportunities and limitations.
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Course by
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Self Paced
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16 hours
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English
Probability & Statistics for Machine Learning & Data Science
Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you’ll apply the math concepts you learn using Python programming in hands-on lab exercises.
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Course by
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Self Paced
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29 hours
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English
Deep learning in Electronic Health Records - CDSS 2
Overview of the main principles of Deep Learning along with common architectures. Formulate the problem for time-series classification and apply it to vital signals such as ECG. Applying this methods in Electronic Health Records is challenging due to the missing values and the heterogeneity in EHR, which include both continuous, ordinal and categorical variables. Subsequently, explore imputation techniques and different encoding strategies to address these issues. Apply these approaches to formulate clinical prediction benchmarks derived from information available in MIMIC-III database.
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Course by
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Self Paced
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32 hours
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English
Infectious Disease Transmission Models for Decision-Makers
During the COVID-19 pandemic, both the promise and perils of using infectious disease transmission models to make public health policy decisions became clearer than ever. Optimal use of modeled output requires that public health policy makers be informed consumers of models, that they understand the strengths and limitations of possible approaches, and they know the right questions to ask about the vulnerabilities of the model results.
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Course by
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Self Paced
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4 hours
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English
Predicting Salaries with Decision Trees
In this 1.5 hour long project-based course, you will tackle a real-world prediction problem using machine learning.
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Self Paced
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2 hours
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English
Supervised Machine Learning: Regression and Classification
In the first course of the Machine Learning Specialization, you will: • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online.
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Course by
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Self Paced
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33 hours
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English
Artificial Intelligence Data Fairness and Bias
In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models.
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Course by
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Self Paced
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7 hours
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English
Breast Cancer Prediction Using Machine Learning
In this 2 hours long project-based course, you will learn to build a Logistic regression model using Scikit-learn to classify breast cancer as either Malignant or Benign. We will use the Breast Cancer Wisconsin (Diagnostic) Data Set from Kaggle. Our goal is to use a simple logistic regression classifier for cancer classification. We will be carrying out the entire project on the Google Colab environment. You will need a free Gmail account to complete this project. Please be aware of the fact that the dataset and the model in this project, can not be used in real-life.
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Course by
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Self Paced
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2 hours
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English