JOIN ONE OF THE MOST IN-DEMAND PROFESSION IN IT WORLD
$35.20 Billion
Market Worth by 2027
190,000 to 400,000
More Job Openings by 2027
50 to 65%
Growth by 2027
$105,000
Median Salary
ABOUT THIS COURSE
R is arguably one of the leading languages of Data Science. The powerful functional language offers a complete and verbose ecosystem of packages for data science and statistical computing. In this Course, discover R’s ability to solve challenging problems in exploratory, predictive, and complex data analysis, data visualization, machine learning, and deep learning. Working with state-of-the-art packages and algorithms, learn to answer increasingly difficult questions from the world of big data.
Today, R is the tool of choice for data science professionals in every industry and field. Whether you are full-time number cruncher, or just the occasional data analyst, R will suit your needs. Derived from the professional skills and experience of real-world Data Scientists, this Course will teach you everything you need to succeed as an R Data Scientist today.
This introduction to R programming course will help you master the basics of R. In seven sections, you will cover its basic syntax, making you ready to undertake your own first data analysis using R. Starting from variables and basic operations, you will eventually learn how to handle data structures such as vectors, matrices, data frames and lists. In the final section, you will dive deeper into the graphical capabilities of R, and create your own stunning data visualizations. No prior knowledge in programming or data science is required.
What makes this course unique is that you will continuously practice your newly acquired skills through interactive in-browser coding challenges using the DataCamp platform. Instead of passively watching videos, you will solve real data problems while receiving instant and personalized feedback that guides you to the correct solution.
Intern Program
When you graduate, you could work remotely as a freelancer or as a full-staff at GreaterHeight Academy for up to 3–4 months as a paid intern.
Certificates
The course is a package of more than 70 hours of instructor-led training and 130+ hours of hand-on. Once you meet the requirements of the program, you will receive Greaterheight Academy's certificate stating that you have acquired the skillset of a R Data Scientist.
1-on-1 Mentorship
You will get one-on-one help from our mentor(s) and student instructors who will be in charge of reviewing your codes and all of your exercises and project assignments at Greaterheight Academy.
Develop Your Skill
Become R Data Scientist. R has a strong support for complex data analysis, data visualization, machine learning, and deep learning. You will be learning the best practices and common principals about analysing unstructured and structured data for business analysis and predicting.
Who Should Attend This Course
Being a R Data Scientist professional is the perfect amalgam of experience, Become R Data Scientist development knowledge, and the correct tools/ technologies. It is a good career choice for both newbies and experienced professionals who have industry knowledge. Aspiring professionals of any educational background with an IT professional / massive data sets with parallel and analytical frame of mind are most suited to pursue this path. We would recommend this path strongly for professionals in the following roles:
- Beginners who want to become R Data Scientist
- IT professionals/Developers.
- Freshers into data analytics Programs.
CAREER SUPPORT
We provide each of our R Data Scientist graduates with access to job readiness training, connections to employers and opportunity to hone new skills.
Job Preparation
Build a strong resume with one-on-one coaching support. Learn how to present your code and discuss open source contributions.
Career Resources
Visit development teams at local companies. Attend panel discussions with industry experts.
Networking Opportunities
Showcase your work to potential employers in our global network. Get to know members of your local tech community.
STUDENT LIFE
We break up our daily schedule with a mix of presentations, interactive labs and project collaboration, no two days look exactly alike, but here's an example of what your day could look like on campus.
9
am
Review
Group Review
Daily review and code exercises that reinforce concepts and activities
10
am
Class
Instructor-guided Lessons & Activities
Learn key objectives through lectures, discussions, and activities
12
noon
Lunch
Panel Discussion
Hear from industry insiders during talks and panel discussions (recurring)(Optional)
2
pm
Labs & Exercises
Student-guided Group Activities
Practice new skills, work on labs solo or in groups, & receive instructions on key topics.
5
pm
One-on-Ones
Catch-up on Goals & Progess
Personal review and support from instructors
6
pm
Homework
Panel Discussion
Evening TAs are on hand to support the class in completing daily assignment and review exercises
Career Services
Our experienced team works directly with each student to ensure they are able to excel in their career search and negotiate multiple offers.
Online Presence
By graduation, you will have a strong, unique R Data Scientist Programming portfolio, online profiles and a resume that reflects your value in the job market.
98%
Graduate Hiring Guaranteed
N150,000+
Avg Graduate Salary
50+
Partners & Collaborators
Online Presence
Our instructional staff conducts mock interviews, training exercises and role-play sessions designed to help you tackle the job interview.
WHAT YOU WLL LEARN
Gain a mastery of the skills you need to land a job as a R Data Scientist. GreaterHeight Academy teaches the in-demand skills you need to become R Data Scientist Stack in just 4 to 6 months, and you will learn the following from fundamentals through advance, depending on your receptiveness to teaching and mentoring:
R Data Science Principles
The R language is the most widely used language in the field of statistical computation and data science. In this course, you’ll perform data science tasks by taking advantage of R’s powerful ecosystem of packages and to turn raw, unstructured data into valuable insights. Learn the essential and fundamental concepts in data mining, statistical modeling, and simulation, along with the strategy to solve predictive modeling problems.
What will I be able to do?
Get to know the advanced features of R including high-performance computing; Design statistical solutions with R and solve
scientific and real-world problems; Familiarize yourself with algorithms written in R for spatial data mining, text mining, and
web data mining; Get acquainted with some of the highly efficient R packages; and Discover the different approaches of tagging
text.
The Course includes:
Simulation for Data Science with R
Learning Data Mining with R
Mastering Text Mining with R
Data Analysis With R
In this course, work with data effectively using crucial R packages designed to make data analysis fast, accurate, and concise. Use the essential R tools required to analyze data and learn all about Bayesian methods and advanced predictive analytics.
What will I be able to do?
Grow your expertise in using R and its diverse range of packages; Gain a thorough understanding of statistical reasoning and sampling;
Perform Bayesian Inference on massively large data sets; Recognize the assumptions, strengths, and weaknesses of a predictive model;
and Get acquainted with Probability Theory to predict and explore discrete variables.
Data Visualization with R
R Data Visualization offers hands-on, practical recipes to guide you in your day-to-day learning. Get to grips with critical data visualization techniques to create interactive visuals to help explain complex data with ease and accuracy.
What will I be able to do?
Create presentations and learn the basics of creating apps in R, Design interactive visualizations and integrate them on your website
or blog, Explore data manipulation techniques while creating meaningful visualizations, and Communicate and tell a story using visualization
techniques.
The Course includes:
R Data Visualization Practical
Machine Learning with R
Machine learning is one of the most important techniques in the modern world. It is widely used across different organizations to optimize, predict, and forecast business critical information. With this Course, explore powerful machine learning algorithms and popular recommendation packages in R.
What will I be able to do?
Harness the power of R to build machine learning algorithms, Build decision rules and support vector machines by predicting values using R,
Understand the concepts of PGM, Transform the old linear regression model into a powerful probabilistic model, and Understand how to optimize
it to build efficient recommendation systems
Deep Learning with R
Deep learning is currently one of the hottest and emerging topics in Data Science. Push yourself to the next level of artificial intelligence and extract, automate, and discover accurate results of the highest level. Use the deep learning package H2O and tune and optimize your models like never before.
What will I be able to do?
Set up the R package H2O to train deep learning models, Use Autoencoders to identify anomalous data or outliers, Predict or classify data
automatically using deep neural networks, and Build generalizable models using regularization to avoid overfitting the training data.
The Course includes:
R Deep Learning Essentials
Hadoop Basics
The volume of data that is made publicly available is increasing every year. Success now and in the future will be measured by an individual’s ability to extract value from large data sets. The larger the data, the more difficult it becomes to manage the types of data collected, that is, it will be messy, unstructured, and complex. Starting with the fundamentals, this Course gets you started with Hadoop and helps develop your skills when tackling and working with big data problems.
What will I be able to do?
Use the unique features of Hadoop 2 to model and analyze, Go beyond MapReduce and process data in real time with Spark, Build data
processing flows using Apache Pig, Understand the fundamentals of HBase and get to grips with the HBase data model, and Manage big
data clusters efficiently using the YARN framework.
The Course includes:
Learning Hadoop 2
Learning HBase
Spark Fundamentals
Spark is an open source cluster computing system that is designed to process large datasets with high speed and ease of development. Spark was developed as a standalone platform that makes use of large scale data analysis in real time. In this card, learn about Spark’s in-memory analytics, which pretty much allows it to process data as fast as possible. Learn all about Spark’s Machine Learning Library and how you can run the Spark framework on top of Hadoop clusters.
What will I be able to do?
Query Spark with a SQL-like query syntax; Discover Spark stream processing via Flume, HDFS; Examine clustering and classification using
MLlib; Perform large-scale graph processing and analysis with GraphX; and Combine Spark with H20 and deep learning.
The Course includes:
Fast Data Processing with Spark
Download our full curriculum to see what we teach week-by-week!
APPRENTICESHIP
Beyond the classroom, the Apprenticeship emphasizes real-world work experience, collaboration with a team of developers, project planning and management, and pair programming, as well as interview and resume preparation. By building professional experience into the GreaterHeight Academy program, we ensure that our developers continue to grow after class-room interactions. Every day apprenticing makes you more competitive in the industry and more likely to land the R Data Scientist position of your dreams.
GreaterHeight
Technologies
Our independent GreaterHeight Technologies, GreaterHeight Technologies, to provide GreaterHeight Academy graduates with the professional experience they need to launch their coding careers. Our developers deliver polished web applications to clients.
Work Alongside
Experienced Devs
During your R Data Scientist apprenticeship, you'll pair program with the agency's more experienced Business Analyst. This opportunity allows apprentices to learn from senior devs hands-on, plus gain experience programming in pairs - a common industry practice.
Job Prep
Curriculum
Your apprenticeship with Greaterheight Academy also includes our three-part job-prep curriculum. You'll learn how to land interviews, improve the soft skills employers look for, and master R Development and technical topics likely to come up in interviews.
BENEFITS
GUARANTEED
EXPERIENCE
Guaranteed way to gain real-world experience in your new profession and build an impressive R Data Scientist Stack portfolio.
TEAM
COLLABORATION
Learn skills you can't get in a classroom: team collaboration, working with clients, agile, and more.
PROFESSIONAL
MENTORING
Gain knowledge from experienced professional developers throughout your apprenticeship.
SELF
CONFIDENCE
Gain confidence and prove to yourself that you are now a professional R Data Scientist Stack developer.
TUITION
N550,000
Financing Available
Financing plans available through Greaterheight Academy and our hand-selectd financing partners, Skins Funds. Repayment period ranged from 0-5years with monthly payments as low as N20,000.00. Contact your Student Advisor for details.
We stand by your results
Get a job creating software upon graduation, or we will refund your tuition in full. See details
Payment Plans
Tuition can be paid upfront or over six installments. The installment plan: one payment of 50% of the program cost fee upon enrollment, and monthly installments of 10% until the Tuition is fully paid. We accept credit cards, debit cards, checks, and PayPal.
Scholarships
Diversity and Merit Based Scholarships available. Attend an info session to learn more.
Refund Policy
We'll provide you with a full refund if you drop out within 7 days of starting your course. If you choose to drop out later, you will receive a pro-rated refund based on the number of days you've spent in the program, minus a non-refundable 10% of program cost fee.
FUND YOUR FUTURE
Need payment assistant? or financing options allow you to focus on you goals instead of the barrier that stop you from reaching them.
Future Finance
Apply for fixed and term based merit loan
GET THE INFO FROM AN EXPERT
Dive deep into the curriculum, the course structure, and what you can achieve from a course mentor.
See if this program is a fit for you. Meet the GreaterHeight team, get an overview of the program curriculum, and chat with other students thinking about this program.
Become An R Data Scientist information Session
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FAQs
We love questions, almost as much aswelove providing answers.Here are a few samplings of what we're typically asked, along with our responses.
By the end of this lesson, you will be able to design a Web Apps as you master the followings:
- Get to know the advanced features of R including high-performance computing
- Design statistical solutions with R and solve scientific and real-world problems
- Familiarize yourself with algorithms written in R for spatial data mining, text mining, and web data mining
- Get acquainted with some of the highly efficient R packages
- Discover the different approaches of tagging text
- Grow your expertise in using R and its diverse range of packages
- Gain a thorough understanding of statistical reasoning and sampling
- Perform Bayesian Inference on massively large data sets
- Recognize the assumptions, strengths, and weaknesses of a predictive model
- Get acquainted with Probability Theory to predict and explore discrete variables
- Create presentations and learn the basics of creating apps in R
- Design interactive visualizations and integrate them on your website or blog
- Explore data manipulation techniques while creating meaningful visualizations
- Communicate and tell a story using visualization techniques
- Harness the power of R to build machine learning algorithms
- Build decision rules and support vector machines by predicting values using R
- Understand the concepts of PGM
- Transform the old linear regression model into a powerful probabilistic model
- Understand how to optimize it to build efficient recommendation systems
- Set up the R package H2O to train deep learning models
- Use Autoencoders to identify anomalous data or outliers
- Predict or classify data automatically using deep neural networks
- Build generalizable models using regularization to avoid overfitting the training data
- Use the unique features of Hadoop 2 to model and analyze
- Go beyond MapReduce and process data in real time with Spark
- Build data processing flows using Apache Pig
- Understand the fundamentals of HBase and get to grips with the HBase data model
- Manage big data clusters efficiently using the YARN framework
- Query Spark with a SQL-like query syntax
- Discover Spark stream processing via Flume, HDFS
- Examine clustering and classification using MLlib
- Perform large-scale graph processing and analysis with GraphX
- Combine Spark with H20 and deep learning
View All FAQs
