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دوراتنا
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).
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Course by
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الإنجليزية
Data Mining Pipeline
This course introduces the key steps involved in the data mining pipeline, including data understanding, data preprocessing, data warehousing, data modeling, interpretation and evaluation, and real-world applications. 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.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية
Web of Data
This MOOC – a joint initiative between EIT Digital, Université de Nice Sophia-Antipolis / Université Côte d'Azur, and INRIA - introduces the Linked Data standards and principles that provide the foundation of the Semantic web. You will learn how to publish, obtain and use structured data directly from the Web.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Data Mining for Smart Cities
Internet of things (IoT) has become a significant component of urban life, giving rise to “smart cities.” These smart cities aim to transform present-day urban conglomerates into citizen-friendly and environmentally sustainable living spaces. The digital infrastructure of smart cities generates a huge amount of data that could help us better understand operations and other significant aspects of city life. In this course, you will become aware of various data mining and machine learning techniques and the various dataset on which they can be applied.
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Course by
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Self Paced
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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.
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Course by
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Self Paced
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21 ساعات
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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.
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Course by
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Self Paced
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28 ساعات
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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.
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Course by
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Self Paced
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14 ساعات
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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.
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Course by
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Self Paced
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24 ساعات
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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.
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Course by
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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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Course by
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Self Paced
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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.
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Course by
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Self Paced
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الإنجليزية
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.
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Course by
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Self Paced
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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.
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Course by
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Self Paced
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الإنجليزية
Big Data Fundamentals
Learn how big data is driving organisational change and essential analytical tools and techniques, including data mining and PageRank algorithms.
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Course by
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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.
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Course by
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Self Paced
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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.
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Course by
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Self Paced
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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.
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Course by
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Self Paced
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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.
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Course by
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Self Paced
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الإنجليزية
Plant Bioinformatics Capstone
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.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Twitter API: Mining Data using Orange Data Mining Platform
In this one hour long project, you will mine, analyze and visualize various trending tweets using Word Cloud, Heat map, Document Map and perform sentiment analysis using Orange. Orange is an open-source data visualization, machine learning and data mining toolkit. Without any prior programming experience, Orange allows you to mine Twitter. If you are a corporate employee, marketer, or even a student who wants to explore how to mine tweets, Orange is the best platform for it.
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Course by
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Self Paced
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3 ساعات
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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.
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Course by
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Self Paced
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9 ساعات
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الإسبانية
Data Warehousing and Business Intelligence
This course builds on “The Nature of Data and Relational Database Design” to extend the process of capturing and manipulating data through data warehousing and data mining. Once the transactional data is processed through ETL (Extract, Transform, Load), it is then stored in a data warehouse for use in managerial decision making. Data mining is one of the key enablers in the process of converting data stored in a data warehouse into actionable insight for better and faster decision making.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
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 ساعات
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الإنجليزية
Assessment for Data Analysis and Visualization Foundations
This course is the final step in the Data Analysis and Visualization Foundations Specialization. It contains a graded final examination that covers content from three courses: Introduction to Data Analytics, Excel Basics for Data Analysis, and Data Visualization and Dashboards with Excel and Cognos. From the Introduction to Data Analytics course, your understanding will be assessed on topics like the data ecosystem and the fundamentals of data analysis, covering tools for data gathering and data mining.
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Course by
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Self Paced
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1 ساعات
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الإنجليزية
Business intelligence and data warehousing
Welcome to the specialization course Business Intelligence and Data Warehousing. This course will be completed on six weeks, it will be supported with videos and various documents that will allow you to learn in a very simple way how to identify, design and develop analytical information systems, such as Business Intelligence with a descriptive analysis on data warehouses.
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Course by
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Self Paced
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10 ساعات
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الإنجليزية