Data Science with R

A short course to learn data science in R from scratch.


ByMannem Reddy, Senior Data Scientist @ Maxis
Artificial IntelligenceData Science & Analytics

This course will teach you data science and machine learning using R. Perform powerful data analysis on big data sets by mastering this skill!

Course Overview

weekend

Enrolment opens soon!

1 day ,8 hours

PJ Trade Center, Ispace

beginner

Register Interest

see full course

Why you should take this course in machine learning

R is a powerful programming language used widely for data analysis and statistical computing. It was developed in early 90s. Since then, endless efforts have been made to improve R’s user interface. The journey of R language from a rudimentary text editor to interactive R Studio and more recently Jupyter Notebooks has engaged many data science communities across the world. This was possible only because of generous contributions by R users globally. Inclusion of powerful packages in R has made it more and more powerful with time. Packages such as dplyr, tidyr, readr, data.table, SparkR, ggplot2 have made data manipulation, visualization and computation much faster. But, what about Machine Learning ? For a lot of people, the first impression of R was that it is just a software for statistical computing. Good thing, that is wrong! R has enough provisions to implement machine learning algorithms in a fast and simple manner. This is a complete tutorial to learn data science and machine learning using R. By the end of this tutorial, you will have a good exposure to building predictive models using machine learning on your own. No prior knowledge of data science / analytics is required. However, prior knowledge of algebra and statistics will be helpful.

Why you should learn R from Mannem Reddy

Mannem Reddy

Mannem Reddy

Senior Data Scientist @ Maxis

An important part of being a data scientist is being capable of turning dry analysis into an exciting story that influences the direction of the business and communicating with diverse teams to take a project from start to finish.

What you will learn

Introduction to machine learning

Since this is a beginner course, we will start off with a introduction to machine learning. You will learn what machine learning is and where you can apply it. You will discover all the different types of machine learning and study a few user cases in real time.

Basics of R Programming for Data Science

After we have laid out the groundwork, you will discover why you should learn R these days, a brief history of the programming language and an introduction to how it works and it's terminology. You will learn how to install R and how to work with R-studio. Finally you will go into R packages and perform some basic computations.

Essentials of R Programming

In the third module you will learn all about data types and objects in R. You will explore control structures (functions) in R and how to use different useful packages.

Exploratory Data Analysis in R

One of the most exciting parts of R is exploratory data analysis. You will learn how to create beautiful graphics. You will understand how to treat missing values, and learn to work with continuous and categorical variables.

Data manipulation in R

With data manipulation in R you will learn how to do feature engineering, label encoding and one-hot encoding.

Predictive modelling using machine learning in R

Something that cannot be missed in a machine learning course; predictive modelling. You will learn all there is to know about predictive modelling using machine learning in R. Subjects go from linear regression, decision tree to random forest.

Who is this course for?

Developers Fresh graduates Managers
Developers Fresh graduates Managers

This course is intended for learners who have basic programming background, and want to apply statistics, machine learning, information visualization, social network analysis, and text analysis techniques to gain new insight into data. Only minimal statistics background is expected, and the course contains a refresh of these basic concepts. Learners with a formal training in Computer Science but without formal training in data science will still find the skills they acquire in these courses valuable in their studies and careers. Students should bring a laptop.

All the instructors are very helpful and eager to share their knowledge. I learned directly how to apply new knowledge, boosted my network by working on case studies with other attendees and got amazing career guidance by UBARU after the course. Every course feels like it is made for me.

- Ruvina Danaraj - Branding and Partnerships at SOCAR Malaysia.

A day in an UBARU Course

9.00 AM

Class

Learn the key skills and methods through theory lecture, Q&A and activities. You will enjoy a formidable presentation based on the instructors industry expertise. To ensure every chapter is relevant to you, interaction plays a big part.

12.00 PM

Lunch (optional)

Enjoy a fully provided lunch, review the morning session with your classmates and network with the instructors. We will make sure everything gets prepared for the afternoon session. This is also a good time to get some extra help, where needed.

12.45 PM

Practice

Theory is one part, exercise is what is creating a new skill. Practice your new knowledge with real-life case-studies, examples and exercises. Work together in groups, get extra help from the instructor and learn how to apply your new skills in your area of expertise.

6.00 PM

Network (optional)

Optional network session after the course, talk to your instructor, get to know your classmates and expend your professional network. Enjoy our meet ups, open discussions, and happy hours, in our personal after course sessions.

9.00 AM

Class

Learn the key skills and methods through theory lecture, Q&A and activities. You will enjoy a formidable presentation based on the instructors industry expertise. To ensure every chapter is relevant to you, interaction plays a big part.

12.00 PM

Lunch (optional)

Enjoy a fully provided lunch, review the morning session with your classmates and network with the instructors. We will make sure everything gets prepared for the afternoon session. This is also a good time to get some extra help, where needed.

12.45 PM

Practice

Theory is one part, exercise is what is creating a new skill. Practice your new knowledge with real-life case-studies, examples and exercises. Work together in groups, get extra help from the instructor and learn how to apply your new skills in your area of expertise.

6.00 PM

Network (optional)

Optional network session after the course, talk to your instructor, get to know your classmates and expend your professional network. Enjoy our meet ups, open discussions, and happy hours, in our personal after course sessions.

Every course with UBARU is another great experience. Every time I attend, the instructor gives a unique twist to the whole experience. These instructors are the best in their field, and you can definitely see that during the course. When I attend a course in which I have zero experience, the instructors are patient and there to help.

Overall great experience, good vibe and walked away with some good connections due to the networking sessions. Thanks!

- Khaled Emdad - Performance Marketing Manager at Admiral Digital.

Every course with UBARU is another great experience. Every time I attend, the instructor gives a unique twist to the whole experience. These instructors are the best in their field, and you can definitely see that during the course. When I attend a course in which I have zero experience, the instructors are patient and there to help.

Overall great experience, good vibe and walked away with some good connections due to the networking sessions. Thanks!

- Khaled Emdad - Performance Marketing Manager at Admiral Digital.

Frequently Asked Questions

You have a question? We have an answer!

What is the benefit of classroom learning over online courses?

To ensure you get the most out of the course, all our teaching moments are on location in one of our classrooms. Whether you learn something you have never done before or you are enhancing your current skills with an intermediate or expert course, you will get the most out of it by interacting with your instructor and classmates face to face. Also, we strive to make every course as relevant for each attendee as we can. By learning in a classroom you have the chance to get tips and exercises to apply your new knowledge in your field of expertise. We have classroom locations in TTDI and PJ Trade Center. You will find the location for your course in the course overview at the top of the page.

I cannot attend on this date, can I sign up for the next one?

Yes you can! Your time is precious and we understand that. Luckily all our courses are being given on a regular basis. Drop us a message through the contact section below and we will notify you as soon as the next enrolment dates are known!

How do I secure my spot in a course?

To ensure every student gets full attention, guidance and help where needed, all our courses have a limited amount of open seats. We work according to first come, first serve. Your spot in one of our courses, bootcamps, guest lectures or events, is secured as soon as you payed and received your ticket.

Questions?
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