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Our Courses
Analyzing Data with Python
In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn!
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15
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English
AI for Everyone: Master the Basics
Learn what Artificial Intelligence (AI) is by understanding its applications and key concepts including machine learning, deep learning and neural networks.
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33
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English
Introduction to Machine Learning on AWS
This course is intended for software developers and engineers taking their first steps with the AWS services that do much of heavy lifting of Machine Learning for you.
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15
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English
Machine Learning at the Edge on Arm: A Practical Introduction
****This course will provide you with the hands-on experience you’ll need to create innovative machine learning applications using ubiquitous Arm-based microcontrollers.
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8
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English
Robotic process and intelligent automation for finance
In this course we explain how automation can play a key role in delivering the requirement to have robust processes and clean data. By using automation tools and machine learning, finance leaders can identify, impl
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Self Paced
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15
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English
Machine learning with Python for finance professionals
A machine learning course focused on delivering practical Python skills for finance professionals looking to maximise their use of these time-saving tools within their organisation.
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Self Paced
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English
Dynamic Programming: Applications In Machine Learning and Genomics
Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.
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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
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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Self Paced
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13 hours
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English
IBM Introduction to Machine Learning
Machine learning skills are becoming more and more essential in the modern job market. In 2019, Machine Learning Engineer was ranked as the #1 job in the United States, based on the incredible 344% growth of job openings in the field between 2015 to 2018, and the role’s average base salary of $146,085 (Indeed). This four-course Specialization will help you gain the introductory skills to succeed in an in-demand career in machine learning and data science.
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Self Paced
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English
Microsoft Azure Data Scientist Associate (DP-100)
This Professional Certificate is intended for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning s…
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Self Paced
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Digital Health
This specialisation introduces students to the emerging and multidisciplinary field of digital health and the role and application of digital health technologies including mobile applications, wearable technologies, health information systems, telehealth, telemedicine, machine learning, artificial intelligence and big data. These digital health technologies are assessed in terms of their opportunities and challenges to address real-world public health and health care system challenges in order to improve the quality, safety and efficiency of these services.
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Self Paced
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English
DevOps on AWS
DevOps on AWS specialization teaches you how to use the combination of DevOps philosophies, practices and tools to develop, deploy, and maintain applications in the AWS Cloud. Benefits of adopting DevOps include: rapid delivery, reliability, scalability, security and improved collaboration. The first course introduces you to essential AWS products, services, and common solutions.
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Self Paced
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English
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, the…
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Introduction to Machine Learning: Supervised Learning
In this course, you’ll be learning various supervised ML algorithms and prediction tasks applied to different data. You’ll learn when to use which model and why, and how to improve the model performances. We will cover models such as linear and logistic regression, KNN, Decision trees and ensembling methods such as Random Forest and Boosting, kernel methods such as SVM. Prior coding or scripting knowledge is required. We will be utilizing Python extensively throughout the course.
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Self Paced
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40 hours
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English
Matrix Methods
Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction. Optional examples using Python are used to illustrate the concepts and allow the learner to experiment with the algorithms.
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Self Paced
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7 hours
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English
Ethics of Technology
This course explores the ethical implications of data analytics. It connects old ideas – privacy, surveillance, power, justice, accountability, corporate responsibility, stakeholder theory – with new technologies and cases, such as the use of machine learning to predict crime. The course will prepare you to evaluate strategic arguments about the ethics of data analytics and to relate data analytics to ethical concepts so that you approach newer, ambiguous capabilities of technology and artificial intelligence with a critical eye.
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Self Paced
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16 hours
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English
Data Science: Machine Learning
Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.
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25
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English
Cloud Machine Learning Engineering and MLOps
Welcome to the fourth course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will build upon the Cloud computing and data engineering concepts introduced in the first three courses to apply Machine Learning Engineering to real-world projects. First, you will develop Machine Learning Engineering applications and use software development best practices to create Machine Learning Engineering applications. Then, you will learn to use AutoML to solve problems more efficiently than traditional machine learning approaches alone.
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12 hours
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English
Data Analysis and Interpretation
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions. The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights.
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Self Paced
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English
Building a Large-Scale, Automated Forecasting System
In this course you learn to develop and maintain a large-scale forecasting project using SAS Visual Forecasting tools. Emphasis is initially on selecting appropriate methods for data creation and variable transformations, model generation, and model selection.
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Self Paced
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10 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
ESG Investing: Financial Decisions in Flux
As ESG investing continues to evolve towards a global standard, certain initiatives such as the UN’s sustainable development goals, and the Paris Agreement on climate change, have already spurred significant changes across the financial markets. As the title of this specialization suggests, financial decisions by investors, as well as capital deployment by companies, organizations, and governments, have been shifting amid increasing attention to environmental, social, and governance-related concerns. By the end of this specialization, students with basic knowledge of traditional financial pr
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Self Paced
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Mathematics for Machine Learning and 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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Self Paced
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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