Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
Text Retrieval and Search Engines
Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.
-
Course by
-
31 ساعات
-
الإنجليزية
Cluster Analysis in Data Mining
Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications.
-
Course by
-
17 ساعات
-
الإنجليزية
Advanced Trading Algorithms
This course will provide back test results for all the strategies in developed and emerging markets. The learner will also be taught scientific ways of back testing without succumbing to either look ahead (or) survival bias. You will learn various methods of building a robust back testing system for the strategies discussed in the previous course. You will be taught how to differentiate between mere data mining and results based on solid empirical or theoretical foundation.
-
Course by
-
Self Paced
-
11 ساعات
-
الإنجليزية
Pattern Discovery in Data Mining
Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery.
-
Course by
-
Self Paced
-
17 ساعات
-
الإنجليزية
Data Visualization
In the era of big data, acquiring the ability to analyze and visually represent “Big Data” in a compelling manner is crucial. Therefore, it is essential for data scientists to develop the skills in producing and critically interpreting digital maps, charts, and graphs. Data visualization is an increasingly important topic in our globalized and digital society. It involves graphically representing data or information, enabling decision-makers across various industries to comprehend complex concepts and processes that may otherwise be challenging to grasp.
-
Course by
-
Self Paced
-
16 ساعات
-
الإنجليزية
Business Intelligence Concepts, Tools, and Applications
This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. Effectively and efficiently mining data is the very center of any modern business’s competitive strategy, and a data warehouse is a core component of this data mining. The ability to quickly look back at early trends and have the accurate data – properly formatted – is essential to good decision making. By enabling this historical overview, a data warehouse allows decision makers to learn from past trends and challenges.
-
Course by
-
Self Paced
-
22 ساعات
-
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.
-
Course by
-
Self Paced
-
22 ساعات
-
الإنجليزية
PostgreSQL for Everybody
Across these four courses, you’ll learn how to use the PostgreSQL database and explore topics ranging from database design to database architecture and deployment. You’ll also compare and contrast SQL and NoSQL approaches to database design. The skills in this course will be useful to learners doing data mining or application development.
-
Course by
-
Self Paced
-
الإنجليزية
Mastering Software Development in R
R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians. This Specialization covers R software development for building data science tools.
-
Course by
-
Self Paced
-
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.
-
Course by
-
Self Paced
-
الإنجليزية
Plant Bioinformatic Methods
The past 15 years have been exciting ones in plant biology. Hundreds of plant genomes have been sequenced, RNA-seq has enabled transcriptome-wide expression profiling, and a proliferation of "-seq"-based methods has permitted protein-protein and protein-DNA interactions to be determined cheaply and in a high-throughput manner.
-
Course by
-
Self Paced
-
الإنجليزية
Data Mining Methods
This course covers the core techniques used in data mining, including frequent pattern analysis, classification, clustering, outlier analysis, as well as mining complex data and research frontiers in the data mining field. 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. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history.
-
Course by
-
Self Paced
-
24 ساعات
-
الإنجليزية
Data mining of Clinical Databases - CDSS 1
This course will introduce MIMIC-III, which is the largest publicly Electronic Health Record (EHR) database available to benchmark machine learning algorithms. In particular, you will learn about the design of this relational database, what tools are available to query, extract and visualise descriptive analytics. The schema and International Classification of Diseases coding is important to understand how to map research questions to data and how to extract key clinical outcomes in order to develop clinically useful machine learning algorithms.
-
Course by
-
Self Paced
-
21 ساعات
-
الإنجليزية
Assessment for Learning
For several decades now, assessment has become an increasingly pressing educational priority. Teacher and school accountability systems have come to be based on analysis of large-scale, standardized summative assessments. As a consequence, assessment now dominates most conversations about reform, particularly as a measure of teacher and school accountability for learner performance. Behind the often heated and at times ideologically gridlocked debate is a genuine challenge to address gaps in achievement between different demographically identifiable groups of students.
-
Course by
-
Self Paced
-
14 ساعات
-
الإنجليزية
Macroeconomic Financial Accounts
This course is primarily aimed at undergraduates attending their final year or University students in monetary and financial economics, international macroeconomics and data mining. Professionals in Government institutions, Central Banks, business and the financial industry, along with other professionals interested in finance and macroeconomics, may also benefit from this course.
-
Course by
-
Self Paced
-
28 ساعات
-
الإنجليزية
IBM Data Analyst Capstone Project
By completing this final capstone project you will apply various Data Analytics skills and techniques that you have learned as part of the previous courses in the IBM Data Analyst Professional Certificate. You will assume the role of an Associate Data Analyst who has recently joined the organization and be presented with a business challenge that requires data analysis to be performed on real-world datasets.
-
Course by
-
Self Paced
-
21 ساعات
-
الإنجليزية
Mejores Decisiones con Business Analytics
Con este curso de: Mejores decisiones con Business Analytics, lograremos identificar su importancia, tipos y aplicaciones en el desarrollo actual de los negocios. Con este objetivo en mente, veremos los conceptos generales de Business Analytics y su evolución. También profundizaremos en la analítica descriptiva y su aplicabilidad.
-
Course by
-
Self Paced
-
9 ساعات
-
الإسبانية
Data Mining Foundations and Practice
The Data Mining specialization is intended for data science professionals and domain experts who want to learn the fundamental concepts and core techniques for discovering patterns in large-scale data sets.
-
Course by
-
Self Paced
-
الإنجليزية
IBM Data Science
Prepare for a career in the high-growth field of data science. In this program, you’ll develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist in as little as 4 months. No prior knowledge of computer science or programming languages is required. Data science involves gathering, cleaning, organizing, and analyzing data with the goal of extracting helpful insights and predicting expected outcomes.
-
Course by
-
Self Paced
-
الإنجليزية
Analytics for Decision Making
The field of analytics is typically built on four pillars: Descriptive Analytics, Predictive Analytics, Causal Analytics, and Prescriptive Analytics. Descriptive analytics (e.g., visualization, BI) deal with the exploration of data for patterns, predictive analytics (e.g., data mining, time-series forecasting) identifies what can happen next, causal modeling establishes causation, and prescriptive analytics help with formulating decisions. This specialization focuses on the Prescriptive Analytics (the final pillar).
-
Course by
-
الإنجليزية
Big Data Fundamentals
Learn how big data is driving organisational change and essential analytical tools and techniques, including data mining and PageRank algorithms.
-
Course by
-
الإنجليزية
Database systems
This specialized program is aimed at computer people who want to enter the field of information systems and learn their different types of requirements, architectures, performance, techniques and tools so you can know when to use business intelligence, data mining, data science, databases , databases in memory or big data in order to have reliable, maintainable and scalable data intensive systems.
-
Course by
-
Self Paced
-
الإنجليزية
Data Science at Scale
Learn scalable data management, evaluate big data technologies, and design effective visualizations. This Specialization covers intermediate topics in data science. You will gain hands-on experience with scalable SQL and NoSQL data management solutions, data mining algorithms, and practical statistical and machine learning concepts. You will also learn to visualize data and communicate results, and you’ll explore legal and ethical issues that arise in working with big data.
-
Course by
-
Self Paced
-
الإنجليزية
Informed Clinical Decision Making using Deep Learning
This specialisation is for learners with experience in programming that are interested in expanding their skills in applying deep learning in Electronic Health Records and with a focus on how to translate their models into Clinical Decision Support Systems. The main areas that would explore are: Data mining of Clinical Databases: Ethics, MIMIC III database, International Classification of Disease System and definition of common clinical outcomes.
-
Course by
-
Self Paced
-
الإنجليزية
Data Mining
The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp. Courses 2 - 5 of this Specialization form the lecture component of courses in the online Master of Computer Science Degree in Data Science.
-
Course by
-
Self Paced
-
الإنجليزية