Training in Big Data Analytics & Data Visualization with R programming
Course Objective
Hands on program for learning programming in R-Statistical and Data Science programming language for big data analytics techniques & advanced Data Visualisation.You will learn to use R for very fast, easy and efficient data mining, cleaning, analysis and advanced visualization on large data sets.
Suitable For
For executives and researchers engaged in and/or interested to work on large data sets quickly using advanced analytics as well as Visualization techniques for faster, easier and better Interpretation and Reporting across different functionalities.Starting step for those pursuing Data Science, Machine Learning, AI.
Ambeone’s Certification Training in “Big Data Analytics & Visualization using R programming”
R is a powerful language for statistical modeling, data mining, data manipulation & exploration. Also, it is one the most advanced language for data visualization.
R is suitable for Non-IT Managers who do not want to get into too much coding and programming and want to focus on data analysis, data mining & data visualization.
In other words, R is today’s excel and much more!
Hence it is an essential step for those interested in the field of Data Analytics and Data Science to train in Programming with R for Advanced Analytics & Visualization in Dubai.
The program provides you expertise in Quick & High-End Analytics & modeling and is the starting step for learning Machine Learning & Artificial Intelligence.
R and Python are two key languages in the Big Data Analytics & Visualization in Data Science Domain and are critical component for developing expertise in Machine Learning and Artificial Intelligence.
Learning to program with R or Python or both for Big Data Analytics have their own advantages and usage and we believe that mastering them gives a strong hold for developing a career as a Data Scientist.
We offer the above module with Python programming as well.
This course can also be taken in conjunction with professionals management programs like Market Research, Marketing Strategy,HR Analytics, Data Driven Decision Making , Negotiation Skills , Supply Chain Logistics etc. to ensure the advanced analytics and visualization skills are used to enhance the subject domain expertise with efficient and effective use of data.
Topics Covered in our certification Training in Programming with R for Big Data Analytics & Visualization
- Basics of Data Analytics (Level I)
- Basics – Vectors, Matrices, Factors, Data Frames, etc.
- Relational Operators, Equalities, Logical Operators
- Conditional & Control – If Statements, Loops, Writing Functions
- The Apply Family of Functions
- DPLYR Package – Grammar of Data Manipulation
- The Pipe Operator, Group_by & Summarize Operators
- GGPLOT2 & GGVIS packages for data visualization
- PLOTLY Package for interactive data visualization
- R-Shiny – Making customized interactive BI Dashboards
- Cleaning Data with Tidyverse, reshape3, stringR, etc.
- Connecting with SAS, SPSS, SQL Databases, etc.
- Other Important Packages & Programming Concepts.
Our carefully planned and recommended learning structure for Data Science Series
Level | Course Name | Know More |
---|---|---|
Level I | Fundamental of Data Analytics & Interpretation ,Simple Measures of Data | Click here |
Level II | Business Analytics with KPI Measurement using Statistics | Click here |
Level III | Statistics for Data Analytics & Data Science | Click here |
Level IV | Big Data Analytics & Visualization with R | Click here |
Level V | Advanced Data Mining & Manipulation with Python | Click here |
Level VI | Predictive Modeling & Evaluation with Machine Learning | Click here |
Level VII | Advance Machine Learning and Artificial Intelligence with R & Python | Click here |
Level VIII | Applied Analytics-Using Data Science & Machine Learning in Business Analytics | Click here |
Level IX | Neural Network & Unsupervised Learning for Advanced AI | Click here |
Course Duration
32 hours of Instructor Led Sessions
+
40-50 hours of Assignments & Projects
Course Format
5 days intensive Bootcamps/Workshops for Corporate batches
or
Weekend Sessions for Public batches
Course Pre-requisite
There are no pre-requisites for this course.
However it will be beneficial if the participants have some business and analysis experience in order to understand applications of R for statistical techniques in business environments.
In addition, it is advisable for participants to complete our course on Foundation in Statistics, if they wish to pursue Data Science domain.
Course Schedule for Training in Programming with R for Big Data Analytics & Visualization
Course | Course Format | Start Date | Duration | Register |
---|---|---|---|---|
Programming in Python | Weekend Afternoon | 2nd June 2024 | 6 Weeks | Register Here |
Big Data Analytics with R | Weekend Afternoon | 18th June 2024 | 6 Weeks | Register Here |
Programming in Python | Weekend Afternoon | 23rd June 2024 | 6 Weeks | Register Here |
Course Details
- Duration of the course is 32 hours of Instructor Led Class Room code-along Training with 40 hours of self/group study with assignments Hours.
- Students have to submit a Capstone project using R programming for Advanced Analytics & Visualization.
- This course is offered as,
- 5 Day Intensive Boot-Camp.
- Evening Classes. Two 2-hour sessions a week for Eight weeks in the evenings.
- Once a week, Four Hours Classes during Weekends for Eight Weeks
- As part of our ‘Advance Program in Data Science and AI’
- We currently offer this course Dubai, Abu Dhabi, Delhi, Mumbai, Bangalore and Nigeria.
- Checkout our course schedule more information.
- Participants must bring their own laptop. Preferably with more than 8GB ram.
- This course will be taught using R as the programming language.
- All softwares and Databases used for the course are open-source and participants will be taught how to install and set-up the environment.
- All training topics covered in the course will be taught using relevant industry specific case studies and examples.
- This training course is very hands-on/practical and is not a lecture or seminar. Participants will be expected to complete exercises and case studies on their own with necessary support and guidance from the instructor.