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Our Courses
Tools and Practices for Addressing Pandemic Challenges
An overview of the tools, techniques, and practices that can be enacted by policy makers, countries, and organizations to monitor, manage, and react to pandemics and mitigate and govern their impacts. An introductory, multidisciplinary course covering data science, social science, healthcare, and management, paving the way to various courses on specific matters. This course is part of the research project 'Pan-European Response to the Impacts of the COVID-19 and future Pandemics and Epidemics' (PERISCOPE, https://www.periscopeproject.eu/).
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Course by
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Self Paced
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4 hours
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English
C Programming: Pointers and Memory Management - 4
In this course, we will examine a key concept, foundational to any programming language: the usage of memory. This course builds upon the basic concept of pointers, discussed in C Programming: Modular Programming and Memory Management, and introduces the more advanced usage of pointers and pointer arithmetic. Arrays of pointers and multidimensional arrays are addressed, and you will learn how to allocate memory for your own data during program execution.
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Course by
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Self Paced
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7 hours
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English
Ethical Issues in Data Science
Computing applications involving large amounts of data – the domain of data science – impact the lives of most people in the U.S. and the world. These impacts include recommendations made to us by internet-based systems, information that is available about us online, techniques that are used for security and surveillance, data that is used in health care, and many more.
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Course by
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Self Paced
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24 hours
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English
Data Science Ethics
What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values.
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Course by
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Self Paced
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15 hours
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English
Intro to Analytic Thinking, Data Science, and Data Mining
Welcome to Introduction to Analytic Thinking, Data Science, and Data Mining. In this course, we will begin with an exploration of the field and profession of data science with a focus on the skills and ethical considerations required when working with data. We will review the types of business problems data science can solve and discuss the application of the CRISP-DM process to data mining efforts.
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Course by
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Self Paced
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7 hours
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English
Data Science Tutorial
Start learning Data science with the W3Schools course. Data Science is about data gathering, analysis and decision-making. Data Science is about finding patterns in data, through analysis, and make future predictions. This is a structured and interactive version of the W3Schools Data science Tutorial. The course is self-paced with text based modules, practical interactive examples and exercises to check your understanding as you progress. W3schools is the world's largest web developer learning site. Start learning with our proven tutorials used by millions of learners!
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Course by
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Self Paced
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7 hours
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English
Data Science for Business Innovation
This is your chance to learn all about Data Science for Business innovation and future-proof your career. Match your business experience tech and analytics! The Data Science for Business Innovation nano-course is a compendium of the must-have expertise in data science for executives and managers to foster data-driven innovation. The course explains what Data Science is and why it is so hyped.
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Course by
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Self Paced
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7 hours
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English
Data Science at Scale - Capstone Project
In the capstone, students will engage on a real world project requiring them to apply skills from the entire data science pipeline: preparing, organizing, and transforming data, constructing a model, and evaluating results. Through a collaboration with Coursolve, each Capstone project is associated with partner stakeholders who have a vested interest in your results and are eager to deploy them in practice. These projects will not be straightforward and the outcome is not prescribed -- you will need to tolerate ambiguity and negative results!
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Course by
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Self Paced
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6 hours
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English
Unsupervised Algorithms in Machine Learning
One of the most useful areas in machine learning is discovering hidden patterns from unlabeled data. Add the fundamentals of this in-demand skill to your Data Science toolkit. In this course, we will learn selected unsupervised learning methods for dimensionality reduction, clustering, and learning latent features. We will also focus on real-world applications such as recommender systems with hands-on examples of product recommendation algorithms. Prior coding or scripting knowledge is required. We will be utilizing Python extensively throughout the course.
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Course by
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Self Paced
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38 hours
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English
Code Free Data Science
The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data. Predicting future trends and behaviors allows for proactive, data-driven decisions.
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Course by
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Self Paced
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14 hours
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English
Calculus 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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Course by
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Self Paced
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26 hours
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English
AI Workflow: Feature Engineering and Bias Detection
This is the third course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Course 3 introduces you to the next stage of the workflow for our hypothetical media company. In this stage of work you will learn best practices for feature engineering, handling class imbalances and detecting bias in the data. Class imbalances can seriously affect the validity of your
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Course by
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Self Paced
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12 hours
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English
Analyze Datasets and Train ML Models using AutoML
In the first course of the Practical Data Science Specialization, you will learn foundational concepts for exploratory data analysis (EDA), automated machine learning (AutoML), and text classification algorithms. With Amazon SageMaker Clarify and Amazon SageMaker Data Wrangler, you will analyze a dataset for statistical bias, transform the dataset into machine-readable features, and select the most important features to train a multi-class text classifier.
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Course by
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Self Paced
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14 hours
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English
Using Sensors With Your Raspberry Pi
This course on integrating sensors with your Raspberry Pi is course 3 of a Coursera Specialization and can be taken separately or as part of the specialization. Although some material and explanations from the prior two courses are used, this course largely assumes no prior experience with sensors or data processing other than ideas about your own projects and an interest in building projects with sensors. This course focuses on core concepts and techniques in designing and integrating any sensor, rather than overly specific examples to copy.
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Course by
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Self Paced
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9 hours
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English
Extract, Transform, and Load Data
This course is designed for business and data professional seeking to learn the first technical phase of the data science process known as Extract, Transform and Load or ETL. Learners will be taught how to collect data from multiple sources so it is available to be transformed and cleaned and then will dive into collected data sets to prepare and clean data so that it can later be loaded into its ultimate destination. In the conclusion of the course learners will load data into its ultimate destination so that it can be analyzed and modeled.
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Course by
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Self Paced
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15 hours
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English
Julia Scientific Programming
This course introduces you to Julia as a first programming language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics, and many more.
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Course by
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Self Paced
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19 hours
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English
Regression and Classification
Introduction to Statistical Learning will explore concepts in statistical modeling, such as when to use certain models, how to tune those models, and if other options will provide certain trade-offs. We will cover Regression, Classification, Trees, Resampling, Unsupervised techniques, and much more! This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform.
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Course by
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Self Paced
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35 hours
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English
Supervised Text Classification for Marketing Analytics
Marketing data often requires categorization or labeling. In today’s age, marketing data can also be very big, or larger than what humans can reasonably tackle. In this course, students learn how to use supervised deep learning to train algorithms to tackle text classification tasks. Students walk through a conceptual overview of supervised machine learning and dive into real-world datasets through instructor-led tutorials in Python.
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Course by
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Self Paced
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12 hours
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English
Data Science as a Field
This course provides a general introduction to the field of Data Science. It has been designed for aspiring data scientists, content experts who work with data scientists, or anyone interested in learning about what Data Science is and what it’s used for. Weekly topics include an overview of the skills needed to be a data scientist; the process and pitfalls involved in data science; and the practice of data science in the professional and academic world.
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Course by
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Self Paced
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11 hours
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English
MongoDB Aggregation Framework
This course will teach you how to perform data analysis using MongoDB's powerful Aggregation Framework. You'll begin this course by building a foundation of essential aggregation knowledge. By understanding these features of the Aggregation Framework you will learn how to ask complex questions of your data.
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Course by
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Self Paced
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19 hours
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English
Advanced Data Science Capstone
This project completer has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case where he justifies architectural decisions, proves understanding the characteristics of different algorithms, frameworks and technologies and how they impact model performance and scalability.
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Course by
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9 hours
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English
مطوّر الواجهة الخلفية من Meta
Ready to gain new skills and the tools developers use to create websites and web applications?
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Course by
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Self Paced
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Arabic
Curso Completo de Data Science
Este proyecto es un curso práctico y efectivo para aprender Data Science de manera práctica y aplicada.
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Course by
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Self Paced
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3 hours
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Spanish
Ciclo completo del desarrollo de un proyecto de Data Science
En este curso aprenderemos a desarrollar el ciclo completo de la ciencia de datos, desarrollando en profundidad la parte del despliegue del modelo.
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Course by
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Self Paced
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3 hours
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Spanish
Business Transformation with Google Cloud auf Deutsch
Was ist Cloudtechnologie bzw. Data Science und warum ist der Begriff in aller Munde? Welche Vorteile bietet die Cloud für Sie, Ihr Team und Ihr Unternehmen? Wenn Sie sich mit dem Thema Cloudtechnologie vertraut machen möchten, um bessere Arbeit zu leisten, die Zukunft Ihres Unternehmens mitzugestalten und im Zeitalter der Cloud Ihr volles Potenzial zu entfalten, ist der Kurs "Business Transformation with Google Cloud" für Sie die richtige Wahl. In dieser interaktiven Schulung lernen Sie die wichtigsten Cloud-Geschäftsfaktoren kennen, insbesondere Google Cloud.
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Course by
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Self Paced
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18 hours
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German