Data Science Certification Course Using R

Access Duration - 365 Days
4.5( 2 REVIEWS )
129 STUDENTS
£.00
 

What Will I Learn?

Gain an introduction to the Data Science Lifecycle
Gain a complete understanding of the tools and techniques in Data Transformation
Learn to perform Text Mining and Analyses
Gain insight into data visualisation
Learn about SMEs in data science training

Overview

If you wish to become an expert in data science, the Data Science Certification Using R is designed to provide individuals in-detail information on the data science lifecycle and machine learning algorithms. You will learn about different techniques and tools, gain insight into optimisation techniques and learn industry-standard best practices.

The Data Science Certification Using R will cover key topics that will get learners up to date on how to analyse and visualise data sets, learn about Decision Trees, Clustering, Naïve Bayes and Random Forest. Data science refers to a concept that will unify data analysis, statistics and related methods to analyse and understand actual data. You will learn to apply your skills in real-life projects by using different tools to gather to derive insight, and gather data sets and interpret it to make effective decisions.

The Data Science Certification Using R will help you master the skills required to tackle real-life data challenges. Qualifying in this course will set you in the right direction, giving you the opportunity to open the door to new and exciting job roles in data science and analytics.

Why You Should Consider Taking this Course at Global Edulink?

Global Edulink is a leading online provider for several accrediting bodies, and provides learners the opportunity to take this exclusive course awarded by CPD. At Global Edulink, we give our fullest attention to our learners’ needs and ensure they have the necessary information required to proceed with the Course.  Learners who register will be given excellent support, discounts for future purchases and be eligible for a TOTUM Discount card and Student ID card with amazing offers and access to retail stores, the library, cinemas, gym memberships and their favourite restaurants.

  • Access Duration
  • Who is this Course for?
  • Entry Requirement
  • Method of Assessment
  • Certification
  • Awarding Body
  • Career Path & Progression
The course will be directly delivered to you, and you have 12 months access to the online learning platform from the date you joined the course.  The course is self-paced and you can complete it in stages, revisiting the lessons at any time.
This course is recommended for,
  • Data Scientists
  • Business Analysts
  • Analytics Managers
  • Information Architects
  • R Professionals who want to work with Big Data
  • Learners should be over the age of 16, and have a basic understanding of English, ICT and numeracy.
  • A sound educational background is recommended
  • Basic understanding of R is beneficial

In order to qualify in the course ‘Data Science Certification Using R’ successfully, learners will take an online test with each module being rounded off with multiple-choice questions. This online test is marked automatically, so you will receive an instant grade and know whether you have passed the course.

Upon the successful completion of the course, you will be awarded the Data Science Certification Using R by CPD.
CPD is a leading awarding body in the United Kingdom that meets an excellent standard of high quality education. CPD is committed towards the enhancement of proficiency and personal skills in order to develop learners’ skills and abilities. CPD ensures that both practical and academic qualifications assist individuals to re-skill or up-skill and maintain a competitive advantage in their chosen industry.

The Data Science Certification Using R will improve your candidature for a number of jobs in data analytics.  You can study further courses in the same field and enhance your academic expertise in data science, and add this as a valuable skillset on your resume. Your skills will be recognised by leading organisations that give you the opportunity to land a well-paying job. Given below are job titles you can compete for, along with the average UK salary per annum according to https://www.glassdoor.com.

  • Data Analyst - £55,000 (Approximately)
  • Business Analyst - £67,000 (Approximately)
  • Analytics Manager - £79,000 (Approximately)
  • Information Architects - £90,000 (Approximately)

Key Features

Gain an Accredited UK Qualification
Access to Excellent Quality Study Materials
Personalised Learning Experience
Support by Phone, Live Chat, and Email
Eligible for TOTUM Discount Card
UK Register of Learning Providers Reg No : 10053842

Course Curriculum

1: Introduction to Data Science
What is Data Science?
What does Data Science involve?
Era of Data Science
Business Intelligence vs Data Science
Life cycle of Data Science
Tools of Data Science
Introduction to Big Data and Hadoop
Introduction to R
Introduction to Spark
Introduction to Machine Learning
2: Statistical Inference
What is Statistical Inference?
Terminologies of Statistics
Measures of Centers
Measures of Spread
Probability
Normal Distribution
Binary Distribution
3: Data Extraction, Wrangling and Exploration
Data Analysis Pipeline
What is Data Extraction
Types of Data
Raw and Processed Data
Data Wrangling
Exploratory Data Analysis
Visualization of Data
4: Introduction to Machine Learning
What is Machine Learning?
Machine Learning Use-Cases
Machine Learning Process Flow
Machine Learning Categories
Supervised Learning algorithm: Linear Regression and Logistic Regression
5: Classification Techniques
What are classification and its use cases?
What is Decision Tree?
Algorithm for Decision Tree Induction
Creating a Perfect Decision Tree
Confusion Matrix
What is Random Forest?
What is Naive Bayes?
Support Vector Machine: Classification
6: Unsupervised Learning
What is Clustering & its Use Cases?
What is K-means Clustering?
What is C-means Clustering?
What is Canopy Clustering?
What is Hierarchical Clustering?
7: Recommender Engines
What is Association Rules & its use cases?
What is Recommendation Engine & it’s working?
Types of Recommendations
User-Based Recommendation
Item-Based Recommendation
Difference: User-Based and Item-Based Recommendation
Recommendation use cases
8: Text Mining
The concepts of text-mining
Use cases
Text Mining Algorithms
Quantifying text
TF-IDF
Beyond TF-IDF
9: Time Series
What is Time Series data?
Time Series variables
Different components of Time Series data
Visualize the data to identify Time Series Components
Implement ARIMA model for forecasting
Exponential smoothing models
Identifying different time series scenario based on which different Exponential Smoothing model can be applied
Implement respective ETS model for forecasting
10: Deep Learning
Reinforced Learning
Reinforcement learning Process Flow
Reinforced Learning Use cases
Deep Learning
Biological Neural Networks
Understand Artificial Neural Networks
Building an Artificial Neural Network
How ANN works
Important Terminologies of ANN’s

Students feedback

4.5

Average rating (2)
4.5
5 Star
4 Star
3 Star
2 Star
1 Star
    A W

    Ash Watts

    January 03, 2021
    Extensive material

    The material provided a wealth of information on machine learning algorithms. I gained a conceptual understanding of Statistics, Text Mining and Time Series.

    B H

    Blair Hopkins

    November 10, 2020
    Fantastic learning experience

    It was a successful course exploring key topics on data science and what it involves and business intelligence vs. data science.

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