Generative AI for Business Leaders
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How Google does Machine Learning
دوراتنا
Create Your First Multithreaded Application in Java
In this 2-hour long project-based course, you will learn how to create a banking application that uses conditions and locks to ensure thread safety, practice designing programs that take advantage of multiple threads without losing data integrity, and learn how to apply multithreading to your own projects. By the end of the guided project, you will be able to create your own thread-safe Java multithreaded applications.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Cloud Computing Foundations
Welcome to the first course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn how to build foundational Cloud computing infrastructure, including websites involving serverless technology and virtual machines. You will also learn how to apply Agile software development techniques to projects which will be useful in building portfolio projects and global-scale Cloud infrastructures. This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering.
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Course by
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Self Paced
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19 ساعات
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الإنجليزية
Understanding the Enterprise Systems Environment
Understanding the Enterprise Systems Environment is the second course in the SAP Technology Consultant Professional Certificate program. The course builds your understanding of the digital landscape. You’ll explore business processes and organizational alignment. You’ll get an overview of how systems are designed and developed, and consider architecture, infrastructure, application development, data science, cloud, privacy, and security.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Dynamic Programming, Greedy Algorithms
This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. We will also cover some advanced topics in data structures. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform.
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Course by
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Self Paced
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38 ساعات
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الإنجليزية
Fundamentals of Data Visualization
Data is everywhere. Charts, graphs, and other types of information visualizations help people to make sense of this data. This course explores the design, development, and evaluation of such information visualizations. By combining aspects of design, computer graphics, HCI, and data science, you will gain hands-on experience with creating visualizations, using exploratory tools, and architecting data narratives.
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Course by
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التعلم الذاتي
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15 ساعات
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الإنجليزية
The Data Science of Health Informatics
Health data are notable for how many types there are, how complex they are, and how serious it is to get them straight. These data are used for treatment of the patient from whom they derive, but also for other uses. Examples of such secondary use of health data include population health (e.g., who requires more attention), research (e.g., which drug is more effective in practice), quality (e.g., is the institution meeting benchmarks), and translational research (e.g., are new technologies being applied appropriately).
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Course by
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Self Paced
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10 ساعات
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الإنجليزية
C Programming: Advanced Data Types - 5
In this course you will define your own data types in C, and use the newly created types to more efficiently store and process your data. Many programming languages provide a number of built-in data types to store things such as integers, decimals, and characters in variables, but what if you wanted to store more complex data? Defining your own data types in C allows you to more efficiently store and process data such as a customer's name, age and other relevant data, all in one single variable!
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Clinical Natural Language Processing
This course teaches you the fundamentals of clinical natural language processing (NLP). In this course you will learn the basic linguistic principals underlying NLP, as well as how to write regular expressions and handle text data in R. You will also learn practical techniques for text processing to be able to extract information from clinical notes. Finally, you will have a chance to put your skills to the test with a real-world practical application where you develop text processing algorithms to identify diabetic complications from clinical notes.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Preparing for AI-900: Microsoft Azure AI Fundamentals exam
Microsoft certifications give you a professional advantage by providing globally recognized and industry-endorsed evidence of mastering skills in digital and cloud businesses. In this course, you will prepare to take the AI-900 Microsoft Azure AI Fundamentals certification exam. You will refresh your knowledge of fundamental principles of machine learning on Microsoft Azure. You will go back over the main consideration of AI workloads and the features of computer vision, Natural Language Processing (NLP), and conversational AI workloads on Azure.
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Course by
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10 ساعات
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الإنجليزية
Working for a sustainable future: concepts and approaches
In this course, participants are introduced to key notions and concepts evolving in sustainability science that are relevant to all, independent to one's work or field of interest. After having completed the course, participants will have a better understanding of the vocabulary used today and should demonstrate the ability to reflect critically to integrate different perspectives of environmental, social, and economic sustainability to their specific area of interest or research.
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Course by
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Self Paced
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19 ساعات
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الإنجليزية
AI Workflow: AI in Production
This is the sixth 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. This course focuses on models in production at a hypothetical streaming media company. There is an introduction to IBM Watson Machine Learning. You will build your own API in a Docker container and learn how to manage containers with Kubernetes. The course also introduces&nb
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Optimize ML Models and Deploy Human-in-the-Loop Pipelines
In the third course of the Practical Data Science Specialization, you will learn a series of performance-improvement and cost-reduction techniques to automatically tune model accuracy, compare prediction performance, and generate new training data with human intelligence. After tuning your text classifier using Amazon SageMaker Hyper-parameter Tuning (HPT), you will deploy two model candidates into an A/B test to compare their real-time prediction performance and automatically scale the winning model using Amazon SageMaker Hosting.
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Course by
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Self Paced
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11 ساعات
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الإنجليزية
Statistics For Data Science
This is a hands-on project to give you an overview of how to use statistics in data science.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
The Nature of Data and Relational Database Design
This course provides a comprehensive overview of data, various data types, design of databases for storage of data, and creation and manipulation of data in databases using SQL. By the end of this course, students will be able to describe what business intelligence is and how it’s different from business analytics and data science, conduct a basic descriptive statistical analysis and articulate the findings, and differentiate between types of statistics.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Leadership for Cancer Informatics Research
Informatics research often requires multidisciplinary teams. This requires more flexibility to communicate with team members with distinct backgrounds. Furthermore, team members often have different research and career goals. This can present unique challenges in making sure that everyone is on the same page and cohesively working together.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Identifying Patient Populations
This course teaches you the fundamentals of computational phenotyping, a biomedical informatics method for identifying patient populations. In this course you will learn how different clinical data types perform when trying to identify patients with a particular disease or trait. You will also learn how to program different data manipulations and combinations to increase the complexity and improve the performance of your algorithms.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Relational Database Design
Have you ever wanted to build a database but don't know where to start? This course will provide you a step-by-step guidance. We are going to start from a raw idea to an implementable relational database. Getting on the path, practicing the real-life mini cases, you will be confident and comfortable with Relational Database Design. Let's get started! Relational Database Design 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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71 ساعات
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الإنجليزية
Python Project for Data Engineering
Showcase your Python skills in this Data Engineering Project! This short course is designed to apply your basic Python skills through the implementation of various techniques for gathering and manipulating data. You will take on the role of a Data Engineer by extracting data from multiple sources, and converting the data into specific formats and making it ready for loading into a database for analysis. You will also demonstrate your knowledge of web scraping and utilizing APIs to extract data.
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Course by
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Self Paced
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16 ساعات
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الإنجليزية
Data Science in Stratified Healthcare and Precision Medicine
An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine. You will have a hands-on experience of working with such data. And you will learn from leaders in the field about successful case studies.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
MLOps Platforms: Amazon SageMaker and Azure ML
In MLOps (Machine Learning Operations) Platforms: Amazon SageMaker and Azure ML you will learn the necessary skills to build, train, and deploy machine learning solutions in a production environment using two leading cloud platforms: Amazon Web Services (AWS) and Microsoft Azure.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Data Analysis Using Python
This course provides an introduction to basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data. Students will gain skills in data aggregation and summarization, as well as basic data visualization.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Documentation and Usability for Cancer Informatics
Introduction: Cancer datasets are plentiful, complicated, and hold information that may be critical for the next research advancements. In order to use these data to their full potential, researchers are dependent on the specialized data tools that are continually being published and developed. Bioinformatics tools can often be unfriendly to their users, who often have little to no background in programming (Bolchini et al. 2008).
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Course by
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Self Paced
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6 ساعات
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الإنجليزية
Using probability distributions for real world problems in R
By the end of this project, you will learn how to apply probability distributions to solve real world problems in R, a free, open-source program that you can download. You will learn how to answer real world problems using the following probability distributions – Binomial, Poisson, Normal, Exponential and Chi-square. You will also learn the various ways of visualizing these distributions of real world problems.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Preparing for DP-900: Microsoft Azure Data Fundamentals Exam
Microsoft certifications give you a professional advantage by providing globally recognized and industry-endorsed evidence of mastering skills in digital and cloud businesses. In this course, you will prepare to take the DP-900 Microsoft Azure Data Fundamentals certification exam. You will refresh your knowledge of the fundamentals of database concepts in a cloud environment, the basic skilling in cloud data services, and foundational knowledge of cloud data services within Microsoft Azure.
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Course by
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Self Paced
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6 ساعات
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الإنجليزية
AI Workflow: Business Priorities and Data Ingestion
This is the first course of a six part 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. This first course in the IBM AI Enterprise Workflow Certification specialization introduces you to the scope of the specialization and prerequisites. Specifically, the courses in this specialization are meant for practicing data scientists who are knowledgeable about probability, statistics, linear algebra, and Python tooling for data science and ma
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Course by
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Self Paced
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8 ساعات
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الإنجليزية