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via Udemy |
Go to Course: https://www.udemy.com/course/r-complete-data-analysis-solutions/
Certainly! Here's a comprehensive review and recommendation for the Coursera course on data analysis with R: --- **Course Review: Mastering Data Analysis with R on Coursera** If you're seeking a comprehensive, practical, and expertly curated course to master data analysis using R, this Coursera offering is an excellent choice. Designed to cater to learners at various stages, the course combines a rich blend of text, videos, code examples, and assessments to create an engaging learning experience. **What You Will Learn** This course provides a sequential and modular approach to learning data analysis with R. Starting from data preparation and manipulation, you will explore advanced topics such as probability, statistics, classification, regression, clustering, and association rule mining. The course also introduces time series analysis, making it suitable for analyzing financial data and beyond. A highlight is the inclusion of machine learning techniques, giving learners a well-rounded skill set for tackling real-world data problems. **Learning Approach** The course is structured into logical sections that build upon each other, ensuring a gradual and thorough understanding of concepts. Practical solutions are emphasized, with step-by-step instructions showcasing how to handle heterogeneous datasets, perform sophisticated ETL processes using R packages like "dplyr" and "data.table", and confront probability and statistical challenges efficiently. **Expertise of Instructors** The course features renowned experts such as Yu-Wei Chiu, a data science startup founder with deep expertise in big data processing, and Selva Prabhakaran, an experienced data scientist with extensive industry insights. Other instructors, including Tony Fischetti, Viswa Viswanathan, Shanthi Viswanathan, and Romeo Kienzler, bring valuable perspectives from academia, industry, and research, enriching the learning content with real-world applications and cutting-edge techniques. **Content and Resources** This course is a tapestry of knowledge sourced from multiple Packt publications and courses, making it a rich resource for aspiring data scientists. It covers essential topics such as data manipulation, statistical analysis, predictive modeling, and even introduces cutting-edge topics like cloud-scale data mining and deep learning. **Who Should Enroll** Whether you're a beginner eager to learn R or a professional looking to solidify your data analysis skills, this course is suitable. It prepares you for the data science job market, equipping you with practical, industry-relevant skills. Big companies' continued reliance on R makes this course a worthwhile investment in your career. **Recommendation** I highly recommend this course for anyone interested in data analysis and data science with R. Its comprehensive curriculum, expert instructors, and practical emphasis make it stand out. The modular design allows learners to study at their own pace and revisit specific topics as needed. Enroll now to embark on your data analysis journey and transform raw data into actionable insights with R! --- Feel free to ask if you'd like a shorter summary or specific details!
If you are looking for that one course that includes everything about data analysis with R, this is it. Let's get on this data analysis journey together. This course is a blend of text, videos, code examples, and assessments, which together makes your learning journey all the more exciting and truly rewarding. It includes sections that form a sequential flow of concepts covering a focused learning path presented in a modular manner. This helps you learn a range of topics at your own speed and also move towards your goal of solving data analysis problems with R. The R language is a powerful open source functional programming language. R is becoming the go-to tool for data scientists and analysts. Its growing popularity is due to its open source nature and extensive development community. R is increasingly being used by experienced data science professionals instead of Python and it will remain the top choice for data scientists in 2017. Big companies continue to use R for their data science needs and this course will make you ready for when these opportunities come your way. This course has been prepared using extensive research and curation skills. Each section adds to the skills learned and helps us to achieve mastery of data analysis. Every section is modular and can be used as a standalone resource. This course has been designed to include topics on every possible requirement from a data scientist and it does so in a step-by-step and practical manner. This course covers step-by-step and practical solutions to data analysis using R. It covers every required topic and also adds an introduction to machine learning. We will start off with learning how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. An example of data manipulation will be provided, illustrating how to use the "dplyr" and "data.table" packages to efficiently process larger data structures. We will then understand how easily R can confront probability and statistics problems and look at R instructions to quickly organize and manipulate large datasets. We will then learn to predict user purchase behavior by adopting a classification approach and implement data mining techniques to discover items that are frequently purchased together. Finally, we will offer insight into time series analysis on financial data, after which there will be detailed information on the hot topic of machine learning, including data classification, regression, clustering, association rule mining, and dimension reduction. This course has been authored by some of the best in their fields: Yu-Wei, Chiu (David Chiu) Yu-Wei, Chiu (David Chiu) is the founder of LargitData, a start-up company that mainly focuses on providing big data and machine learning products. He specializes in using Spark and Hadoop to process big data and apply data mining techniques for data analysis. Yu-Wei is also a professional lecturer and has delivered lectures on big data and machine learning in R and Python, and given tech talks at a variety of conferences. Selva Prabhakaran Selva Prabhakaran is a data scientist with a large E-commerce organization. In his 7 years of experience in data science, he has tackled complex real-world data science problems and delivered production-grade solutions for top multinational companies. Tony Fischetti Tony Fischetti is a data scientist at College Factual, where he gets to use R everyday to build personalized rankings and recommender systems. Viswa Viswanathan Viswa Viswanathan is an associate professor of Computing and Decision Sciences at the Stillman School of Business in Seton Hall University. In addition to teaching at the university, Viswa has conducted training programs for industry professionals. He has written several peer-reviewed research publications in journals such as Operations Research, IEEE Software, Computers and Industrial Engineering, and International Journal of Artificial Intelligence in Education. Shanthi Viswanathan Shanthi Viswanathan is an experienced technologist who as a consultant, has helped several large organizations, such as Canon, Cisco, Celgene, Amway, Time Warner Cable, and GE among others, in areas such as data architecture and analytics, master data management, service-oriented architecture, business process management, and modeling. Romeo Kienzler Romeo Kienzler is the Chief Data Scientist of the IBM Watson IoT Division and working as an Advisory Architect helping client worldwide to solve their data analysis problems. His current research focus is on cloud-scale data mining using open source technologies including R, ApacheSpark, SystemML, ApacheFlink, and DeepLearning4J. This course is a blend of text, videos, and assessments, all packaged together keeping your journey in mind. It combines some of the best that Packt has to offer in one complete package. It includes content from the following Packt products: R for Data Science Cookbook by Yu-Wei, Chiu (David Chiu)R for Data Science Solutions [video] by Yu-Wei, Chiu (David Chiu)Mastering R Programming [video] by Selva PrabhakaranData Analysis with R by Tony FischettiR Data Analysis Cookbook by Viswa Viswanathan and Shanthi ViswanathanLearning Data Mining with R [video] by Romeo Kienzler