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Our Courses
AI for Medicine
AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This three-course Specialization will give you practical experience in applying machine learning to concrete problems in medicine. These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. If you are new to deep learning or want to get a deeper foundation of how neural networks work, we recommend taking the Deep Learning Specialization.
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Self Paced
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English
Create Machine Learning Models in Microsoft Azure
Machine learning is the foundation for predictive modeling and artificial intelligence. If you want to learn about both the underlying concepts and how to get into building models with the most common machine learning tools this path is for you. In this course, you will learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models. This course is designed to prepare you for roles that include planning and creating a suitable working environment for data science workloads on Azure.
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Self Paced
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13 hours
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English
Python Data Products for Predictive Analytics
Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego. This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy.
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Mind and Machine
This specialization examines the ways in which our current understanding of human thinking is both illuminated and challenged by the evolving techniques and ideas of artificial intelligence and computer science. Our collective understanding of “minds” – both biological and computational – has been revolutionized over the past half-century by themes originating in fields like cognitive psychology, machine learning, neuroscience, evolutionary psychology, and game theory, among others.
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Investment Management with Python and Machine Learning
The Data Science and Machine Learning for Asset Management Specialization has been designed to deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions.By the end of this specialization, you will have acquired the tools required for making sound investment decisions, with an emphasis not only on the foundational theory and underlying concepts, but also on practical applications and implementation.
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Self Paced
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English
Applied Data Science with Python
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language.
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Self Paced
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English
Data Science for Investment Professionals
This Specialization is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how th…
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Self Paced
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English
Unsupervised Text Classification for Marketing Analytics
Marketing data is often so big that humans cannot read or analyze a representative sample of it to understand what insights might lie within. In this course, learners use unsupervised deep learning to train algorithms to extract topics and insights from text data. Learners walk through a conceptual overview of unsupervised machine learning and dive into real-world datasets through instructor-led tutorials in Python. The course concludes with a major project. This course uses Jupyter Notebooks and the coding environment Google Colab, a browser-based Jupyter notebook environment.
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Course by
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Self Paced
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13 hours
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English
NoSQL, Big Data, and Spark Foundations
Big Data Engineers and professionals with NoSQL skills are highly sought after in the data management industry. This Specialization is designed for those seeking to develop fundamental skills for working with Big Data, Apache Spark, and NoSQL databases.
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Self Paced
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English
Machine Learning: Theory and Hands-on Practice with Python
In the Machine Learning specialization, we will cover Supervised Learning, Unsupervised Learning, and the basics of Deep Learning. You will apply ML algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Starting with supervised learning, we will cover linear and logistic regression, KNN, Decision trees, ensembling methods such as Random Forest and Boosting, and kernel methods such as SVM. Then we turn our attention to unsupervised methods, including dimensionality reduction techniques (e.g., PCA), clustering, and recommender systems.
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Self Paced
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English
AI Product Management
Organizations in every industry are accelerating their use of artificial intelligence and machine learning to create innovative new products and systems. This requires professionals across a range of functions, not just strictly within the data science and data engineering teams, to understand when and how AI can be applied, to speak the language of data and analytics, and to be capable of working in cross-functional teams on machine learning projects. This Specialization provides a foundational understanding of how machine learning works and when and how it can be applied to solve problems.
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Self Paced
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English
MATLAB Programming for Engineers and Scientists
This Specialization is designed for learners with little to no programming experience and teaches them to create MATLAB programs that solve real-world engineering and scientific problems. While the focus is on general computer programming principles, the courses also provide in-depth coverage of MATLAB's unique features for engineering and scientific computing. The first course covers basic programming concepts. The second course teaches techniques for using ChatGPT to program more productively.
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Self Paced
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English
Machine Learning for Marketing
Understand the structure and techniques used in Machine Learning, Text Mining, and Decision Science for Marketing. Explore the fascinating world of Machine Learning and its transformative applications in marketing. Explain how analytics and decision science approaches for marketing can enhance the quality of marketing decision-making. Foundation in digital marketing analytics to understand the consumer journey, intent, and activity on your business website.
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Self Paced
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English
Machine Learning Implementation and Operations in AWS
Machine Learning Implementation Operations in AWS is the fifth Course in the AWS Certified Machine Learning Specialty specialization. The course has a major focus on designing and implementing machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 1:00-1:30 Hours Video lectures that provide both Theory and Hands -On knowledge.
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Self Paced
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6 hours
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English
Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs
In this Google Cloud Labs Specialization, you'll receive hands-on experience building and practicing skills in BigQuery and Cloud Data Fusion.
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Self Paced
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English
Exploratory Data Analysis in AWS
Exploratory Data Analysis in AWS is the second course in the AWS Certified Machine Learning Specialty specialization. The main focus of this course is to analyze Data Streams and Data Analytics services in AWS along with exploring Data Analysis in AWS. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 2:00-2:30 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners.
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5 hours
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English
Explainable deep learning models for healthcare - CDSS 3
This course will introduce the concepts of interpretability and explainability in machine learning applications. The learner will understand the difference between global, local, model-agnostic and model-specific explanations. State-of-the-art explainability methods such as Permutation Feature Importance (PFI), Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanation (SHAP) are explained and applied in time-series classification.
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Self Paced
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30 hours
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English
Business Application of Machine Learning and Artificial Intelligence in Healthcare
The future of healthcare is becoming dependent on our ability to integrate Machine Learning and Artificial Intelligence into our organizations. But it is not enough to recognize the opportunities of AI; we as leaders in the healthcare industry have to first determine the best use for these applications ensuring that we focus our investment on solving problems that impact the bottom line. Throughout these four modules we will examine the use of decision support, journey mapping, predictive analytics, and embedding Machine Learning and Artificial Intelligence into the healthcare industry.
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Self Paced
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13 hours
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English
AI Foundations for Everyone
Artificial Intelligence (AI) is no longer science fiction. It is rapidly permeating all industries and having a profound impact on virtually every aspect of our existence. Whether you are an executive, a leader, an industry professional, a researcher, or a student - understanding AI, its impact and transformative potential for your organization and our society is of paramount importance. This specialization is designed for those with little or no background in AI, whether you have technology background or not, and does not require any programming skills.
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Google Cloud Speech API: Qwik Start
This is a self-paced lab that takes place in the Google Cloud console. The Google Cloud Speech API integrates speech recognition into dev apps; you can now send audio/receive a text transcription. Watch these short videos Powerful Speech Recognition Using Google Machine Learning and Google Cloud Speech: Qwik Start - Qwiklabs Preview
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1 hour
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English
Building Cloud Computing Solutions at Scale
With more companies leveraging software that runs on the Cloud, there is a growing need to find and hire individuals with the skills needed to build solutions on a variety of Cloud platforms. Employers agree: Cloud talent is hard to find.
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Data Science: Foundations using R
Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research. Learners who complete this specialization will be prepared to take the Data Science: Statistics and Machine Learning specialization, in which they build a data product using real-world data. The five courses in this specialization are the very same courses that make up the first half of the Data Science Specialization.
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Machine Learning Rock Star – the End-to-End Practice
Machine learning reinvents industries and runs the world. Harvard Business Review calls it “the most important general-purpose technology of our era.” But while there are so many how-to courses for hands-on techies, there are practically none that also serve the business leadership of machine learning – a striking omission, since success with machine learning relies on a very particular project leadership practice just as much as it relies on adept number crunching. By filling that gap, this course empowers you to generate value with ML.
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Achieving Advanced Insights with BigQuery
The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs.
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Self Paced
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8 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