Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
AI for Efficient Programming: Harnessing the Power of LLMs
This course on Artificial Intelligence (AI) for software development explores the use of AI large language models such as ChatGPT, Bard, and others and their potential benefits and challenges.
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Course by
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التعلم الذاتي
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13 ساعات
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الإنجليزية
Business Analytics Executive Overview
Businesses run on data, and data offers little value without analytics. The ability to process data to make predictions about the behavior of individuals or markets, to diagnose systems or situations, or to prescribe actions for people or processes drives business today. Increasingly many businesses are striving to become “data-driven”, proactively relying more on cold hard information and sophisticated algorithms than upon the gut instinct or slow reactions of humans. This course will focus on understanding key analytics concepts and the breadth of analytic possibilities.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
The R Programming Environment
This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings. As the first course in the Specialization, the course provides the essential foundation of R needed for the following courses.
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Course by
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27 ساعات
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الإنجليزية
Information Extraction from Free Text Data in Health
In this MOOC, you will be introduced to advanced machine learning and natural language processing techniques to parse and extract information from unstructured text documents in healthcare, such as clinical notes, radiology reports, and discharge summaries. Whether you are an aspiring data scientist or an early or mid-career professional in data science or information technology in healthcare, it is critical that you keep up-to-date your skills in information extraction and analysis.
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Course by
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Self Paced
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24 ساعات
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الإنجليزية
A Crash Course in Data Science
By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Python for Genomic Data Science
This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
SQL for Data Science
As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
Getting Started with SAS Programming
This course is for users who want to learn how to write SAS programs to access, explore, prepare, and analyze data. It is the entry point to learning SAS programming for data science, machine learning, and artificial intelligence. It is a prerequisite to many other SAS courses. By the end of this course, you will know how to use SAS Studio to write and submit SAS programs that access SAS, Microsoft Excel, and text data.
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Course by
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Self Paced
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25 ساعات
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الإنجليزية
Excel Basics for Data Analysis
Spreadsheet tools like Excel are an essential tool for working with data - whether for data analytics, business, marketing, or research. This course is designed to give you a basic working knowledge of Excel and how to use it for analyzing data. This course is suitable for those who are interested in pursuing a career in data analysis or data science, as well as anyone looking to use Excel for data analysis in their own domain.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Introduction to Genomic Technologies
This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed. This is the first course in the Genomic Data Science Specialization.
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Course by
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Self Paced
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6 ساعات
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الإنجليزية
Data Science in Real Life
Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Data Processing and Feature Engineering with MATLAB
In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB to lay the foundation required for predictive modeling. This intermediate-level course is useful to anyone who needs to combine data from multiple sources or times and has an interest in modeling. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background.
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Course by
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Self Paced
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20 ساعات
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الإنجليزية
Identifying the Right Role for Yourself
Data science and artificial intelligence are exciting, growing fields with a lot to offer prospective job seekers. However, even with the massive growth in technology and positions, there are still many barriers to entry. This course explores today’s challenges and opportunities within data science and artificial intelligence, the varying skills and education necessary for some commonly confused positions, as well as the specific job duties associated with various in-demand roles.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Process Mining: Data science in Action
Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains. Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية
Foundations of Data Science: K-Means Clustering in Python
Organisations all around the world are using data to predict behaviours and extract valuable real-world insights to inform decisions. Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government. This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses.
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Course by
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Self Paced
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29 ساعات
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الإنجليزية
Data Wrangling, Analysis and AB Testing with SQL
This course allows you to apply the SQL skills taught in “SQL for Data Science” to four increasingly complex and authentic data science inquiry case studies. We'll learn how to convert timestamps of all types to common formats and perform date/time calculations. We'll select and perform the optimal JOIN for a data science inquiry and clean data within an analysis dataset by deduping, running quality checks, backfilling, and handling nulls.
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Course by
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Self Paced
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16 ساعات
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الإنجليزية
Interviewing, Negotiating a Job Offer, and Career Planning
Prepare yourself for interviewing and landing a job in the DS/AI field. In this course, we will discuss what needs to be done before, during, and after the interview process. We will also provide tips and tricks on how to practice for a major component of data science interviews: the technical interview.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
Building a Data Science Team
Data science is a team sport. As a data science executive it is your job to recruit, organize, and manage the team to success. In this one-week course, we will cover how you can find the right people to fill out your data science team, how to organize them to give them the best chance to feel empowered and successful, and how to manage your team as it grows. This is a focused course designed to rapidly get you up to speed on the process of building and managing a data science team. Our goal was to make this as convenient as possible for you without sacrificing any essential content.
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Course by
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Self Paced
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6 ساعات
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الإنجليزية
Introduction to Machine Learning
This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. In addition, we have designed practice exercises that will give you hands-on experience implementing these data science models on data sets.
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Course by
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Self Paced
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21 ساعات
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الإنجليزية
Introduction to Portfolio Construction and Analysis with Python
The practice of investment management has been transformed in recent years by computational methods. This course provides an introduction to the underlying science, with the aim of giving you a thorough understanding of that scientific basis. However, instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language.
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Course by
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Self Paced
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25 ساعات
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الإنجليزية
Basic Data Processing and Visualization
This is the first course in the four-course specialization Python Data Products for Predictive Analytics, introducing the basics of reading and manipulating datasets in Python. In this course, you will learn what a data product is and go through several Python libraries to perform data retrieval, processing, and visualization. This course will introduce you to the field of data science and prepare you for the next three courses in the Specialization: Design Thinking and Predictive Analytics for Data Products, Meaningful Predictive Modeling, and Deploying Machine Learning Models.
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Course by
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Self Paced
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11 ساعات
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الإنجليزية
Introduction to Big Data
Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Applied Social Network Analysis in Python
This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week introduces the concept of connectivity and network robustness. The third week will explore ways of measuring the importance or centrality of a node in a network. The final week will explore the evolution of networks over time and cover models of network generation and the link prediction problem.
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Course by
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Self Paced
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26 ساعات
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الإنجليزية
Applied Machine Learning in Python
This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. The issue of dimensionality of data will be discussed, and the task of clustering data, as well as evaluating those clusters, will be tackled.
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Course by
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31 ساعات
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الإنجليزية
Big Data Modeling and Management Systems
Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples.
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Course by
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13 ساعات
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الإنجليزية