Generative AI for Business Leaders
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How Google does Machine Learning
دوراتنا
Data Science: Statistics and Machine Learning
Build models, make inferences, and deliver interactive data products. This specialization continues and develops on the material from the Data Science: Foundations using R specialization. It covers statistical inference, regression models, machine learning, and the development of data products. In the Capstone Project, you’ll apply the skills learned by building a data product using real-world data.
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Self Paced
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الإنجليزية
Google Advanced Data Analytics
Get professional training designed by Google and take the next step in your career with advanced data analytics skills. There are over 144,000 open jobs in advanced data analytics and the median salary for entry-level roles is $118,000.¹ Advanced data professionals are responsible for collecting, analyzing, and interpreting extremely large amounts of data.
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الإنجليزية
Player Evaluation, Team Performance and Roster Management
This course will provide students with an introduction to using specific data techniques to address key sports administrative functions in team and roster management. The primary focus is on the use of data analysis in player acquisition and retention, as well as player and coach assessment. Students will learn how the collective bargaining agreement (CBA) and standard player contract (SPC) provide the framework for management decisions in which data analysis play a pivotal role. There is a focus on data science techniques as applied to sports datasets.
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Self Paced
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16 ساعات
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الإنجليزية
Machine Learning with Python
Get ready to dive into the world of Machine Learning (ML) by using Python! This course is for you whether you want to advance your Data Science career or get started in Machine Learning and Deep Learning. This course will begin with a gentle introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning, linear & non-linear regression, simple regression and more. You will then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression.
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Course by
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Self Paced
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33 ساعات
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الإنجليزية
DevOps, DataOps, MLOps
Learn how to apply Machine Learning Operations (MLOps) to solve real-world problems. The course covers end-to-end solutions with Artificial Intelligence (AI) pair programming using technologies like GitHub Copilot to build solutions for machine learning (ML) and AI applications.
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Self Paced
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29 ساعات
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الإنجليزية
AI for Scientific Research
In the AI for Scientific Research specialization, we'll learn how to use AI in scientific situations to discover trends and patterns within datasets. Course 1 teaches a little bit about the Python language as it relates to data science. We'll share some existing libraries to help analyze your datasets. By the end of the course, you'll apply a classification model to predict the presence or absence of heart disease from a patient's health data.
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Self Paced
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الإنجليزية
Data Science Fundamentals
This specialization demystifies data science and familiarizes learners with key data science skills, techniques, and concepts. The course begins with foundational concepts such as analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, and then moves on to compare data science with classical statistical techniques.
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الإنجليزية
Data Science Foundations: Statistical Inference
This program is designed to provide the learner with a solid foundation in probability theory to prepare for the broader study of statistics. It will also introduce the learner to the fundamentals of statistics and statistical theory and will equip the learner with the skills required to perform fundamental statistical analysis of a data set in the R programming language. This specialization 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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الإنجليزية
C Programming: Language Foundations - 2
In this course you will learn to use logical statements and arrays in C. Logical statements are used for decision-making with follow-up instructions, based on conditions you define. Arrays are used to store, keep track of, and organize larger amounts of data. You will furthermore implement some fundamental algorithms to search and sort data. Why learn C? Not only is it one of the most stable and popular programming languages in the world, it's also used to power almost all electronic devices.
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Self Paced
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14 ساعات
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الإنجليزية
Wrangling Data in the Tidyverse
Data never arrive in the condition that you need them in order to do effective data analysis. Data need to be re-shaped, re-arranged, and re-formatted, so that they can be visualized or be inputted into a machine learning algorithm. This course addresses the problem of wrangling your data so that you can bring them under control and analyze them effectively.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
IBM Data Analyst
Prepare for a career in the high-growth field of data analytics. In this program, you’ll learn in-demand skills like Python, Excel, and SQL to get job-ready in as little as 4 months. Data analysis is the process of collecting, storing, modeling, and analyzing data that can inform executive decision-making, and the demand for skilled data analysts has never been greater. This program will teach you the foundational data skills employers are seeking for entry-level data analytics roles.
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التعلم الذاتي
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الإنجليزية
Vital Skills for Data Science
Vital Skills for Data Science introduces students to several areas that every data scientist should be familiar with. Each of the topics is a field in itself. This specialization provides a "taste" of each of these areas which will allow the student to determine if any of these areas is something they want to explore further. In this specialization, students will learn about different applications of data science and how to apply the steps in a data science process to real life data.
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Self Paced
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الإنجليزية
Practical Predictive Analytics: Models and Methods
Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems. Learning Goals: After completing this course, you will be able to: 1.
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7 ساعات
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الإنجليزية
Key Technologies for Business
In this Specialization, we will cover 3 key technologies that are foundational and driving significant growth and innovation. These are Cloud Computing, Data Science, and Artificial Intelligence (AI). Technology is essential for the future of business.
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Self Paced
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الإنجليزية
CertNexus Certified Ethical Emerging Technologist
The Certified Ethical Emerging Technologist (CEET) industry validated certification helps professionals differentiate themselves from other job candidates by demonstrating their ability to ethically navigate data driven emerging technologies such as AI, Machine Learning and Data Science. Organizations and governments are seeking out ethics professionals to minimize risk and guide their decision-making about the design of inclusive, responsible, and trusted technology.
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Self Paced
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الإنجليزية
Essential Causal Inference Techniques for Data Science
Data scientists often get asked questions related to causality: (1) did recent PR coverage drive sign-ups, (2) does customer support increase sales, or (3) did improving the recommendation model drive revenue?
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Self Paced
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3 ساعات
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الإنجليزية
Managing Machine Learning Projects
This second course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the practical aspects of managing machine learning projects. The course walks through the keys steps of a ML project from how to identify good opportunities for ML through data collection, model building, deployment, and monitoring and maintenance of production systems.
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18 ساعات
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الإنجليزية
Programming in Python: A Hands-on Introduction
This specialization is intended for people without programming experience who seek to develop python programming skills and learn about the underlying computer science concepts that will allow them to pick up other programming languages quickly. In these four courses, you will cover everything from fundamentals to object-oriented design. These topics will help prepare you to write anything from small programs to automate repetitive tasks to larger applications, giving you enough understanding of python to tackle more specialized topics such as Data Science and Artificial Intelligence.
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الإنجليزية
AI Workflow: Machine Learning, Visual Recognition and NLP
This is the fourth 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 4 covers the next stage of the workflow, setting up models and their associated data pipelines for a hypothetical streaming media company. The first topic covers the complex topic of evaluation metrics, where you will learn best practices for a number of different metrics including regressi
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
AutoML tools for data science
By the end of this project, you will learn how to perform analysis on data using different python libraries and export reports and visualization without much hassle all this with minimal coding.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Modern Regression Analysis in R
This course will provide a set of foundational statistical modeling tools for data science. In particular, students will be introduced to methods, theory, and applications of linear statistical models, covering the topics of parameter estimation, residual diagnostics, goodness of fit, and various strategies for variable selection and model comparison.
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Course by
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Self Paced
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45 ساعات
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الإنجليزية
Practical Data Science with MATLAB
Do you find yourself in an industry or field that increasingly uses data to answer questions? Are you working with an overwhelming amount of data and need to make sense of it? Do you want to avoid becoming a full-time software developer or statistician to do meaningful tasks with your data? Completing this specialization will give you the skills and confidence you need to achieve practical results in Data Science quickly.
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Self Paced
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الإنجليزية
Data Science Methods for Quality Improvement
Data analysis skills are widely sought by employers, both nationally and internationally. This specialization is ideal for anyone interested in data analysis for improving quality and processes in business and industry. The skills taught in this specialization have been used extensively to improve business performance, quality, and reliability. By completing this specialization, you will improve your ability to analyze data and interpret results as well as gain new skills, such as using RStudio and RMarkdown.
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Self Paced
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الإنجليزية
Expressway to Data Science: Essential Math
Data Science is growing rapidly, creating opportunities for careers across a variety of fields. This specialization is designed for learners embarking on careers in Data Science. Learners are provided with a concise overview of the foundational mathematics that are critical in Data Science. Topics include algebra, calculus, linear algebra, and some pertinent numerical analysis.
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Self Paced
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الإنجليزية
Introduction to Discrete Mathematics for Computer Science
Discrete Mathematics is the language of Computer Science. One needs to be fluent in it to work in many fields including data science, machine learning, and software engineering (it is not a coincidence that math puzzles are often used for interviews). We introduce you to this language through a fun try-this-before-we-explain-everything approach: first you solve many interactive puzzles that are carefully designed specifically for this online specialization, and then we explain how to solve the puzzles, and introduce important ideas along the way.
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Course by
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Self Paced
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الإنجليزية