Data Science Course with R

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Wissenhive's Data Science Training lets you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes using R. Data Science Training encompasses a conceptual understanding of Statistics, Time Series, Text Mining and an introduction to Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases on Media, Healthcare, Social Media, Aviation and HR.

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Overview

Wissenhive's in-depth workshop on Data Science with R will help you master R and use its inbuilt functions and libraries for creating applications and programs for data science. R is a much preferred program because of its robustness, flexibility and ease of coding. Its various techniques such as clustering, time-series analyses and classification techniques, nonlinear/linear modelling and classical statistical tests make it apt for use in the field of statistical computation and data science.

 

What you will learn

  • Tools & Technologies
  • Statistics for Data Science
  • R for Data Science
  • Exploratory Data Analysis
  • Data Visualization using R
  • Advanced Statistics & Predictive Modeling

Benefits

On completing R and knowing the fundamentals of Data science, you can aim for a rewarding career in data science. Since the evolution of big data, data science and data analysis have become the most sought after career paths because of the huge demand for data science professionals. Not only high profile technology companies such as Google and Facebook but companies across sectors are hiring data scientists who can generate business and solve complex data related problems. This is the perfect course for you to step into the world of data science and make a career in what has been rated as the best job in America by Glassdoor.com

  • The number of Data Science and Analytics job listings is projected to grow by nearly 364,000 listings by 2020 - Forbes
  • The average salary for a Data Scientist is $120k as per Glassdoor
  • Businesses analysing data will see $430 billion in productivity benefits over their rivals not analysing data by 2020

 

Course Content

What is Data Science? 15:31 Play
Analytics Landscape 15:32 Play
Life Cycle of a Data Science Project 15:32 Play
Data Science Tools & Technologies 15:32 Play
Introduction to R Programming 15:33 Play
Installing and Loading Libraries 15:33 Play
Data Structures in R 15:33 Play
Control & Loop Statements in R 15:33 Play
Functions in R 15:33 Play
Loop Functions in R 15:33 Play
String Manipulation & Regular Expression in R 15:33 Play
Working with Data in R 15:33 Play
Data Visualization in R 15:33 Play
Case Study 15:33 Play
Measures of Central Tendency 15:35 Play
Measures of Dispersion 15:35 Play
Descriptive Statistics 15:35 Play
Probability Basics 15:35 Play
Marginal Probability 15:35 Play
Bayes Theorem 15:35 Play
Probability Distributions 15:35 Play
Hypothesis Testing 15:35 Play
ANOVA 15:37 Play
Linear Regression (OLS) 15:37 Play
Case Study: Linear Regression 15:37 Play
Principal Component Analysis 15:37 Play
Factor Analysis 15:37 Play
Case Study: PCA/FA 15:37 Play
Logistic Regression 15:38 Play
Case Study: Logistic Regression 15:38 Play
K-Nearest Neighbor Algorithm 15:38 Play
Case Study: K-Nearest Neighbor Algorithm 15:38 Play
Decision Tree 15:38 Play
Case Study: Decision Tree 15:38 Play
Understand Time Series Data 15:39 Play
Visualizing Time Series Components 15:39 Play
Exponential Smoothing 15:40 Play
Holt's Model 15:40 Play
Holt's MoHolt-Winter's Modeldel 15:40 Play
ARIMA 15:40 Play
Case Study: Time Series Modeling on Stock Price 15:40 Play

Course Details

Data science is a "concept to unify statistics, data analysis and their related methods" to "understand and analyse actual phenomena" with data. Data Science Training employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science from the sub-domains of machine learning, classification, cluster analysis, data mining, databases, and visualization. The Data Science Certification Course enables you to gain knowledge of the entire life cycle of Data Science, analyse and visualise different data sets, different Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes.

Who should go for this Data Science Course?

The market for Data Analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Our Data Science Training helps you to grab this opportunity and accelerate your career by applying the techniques on different types of Data. It is best suited for:

  • Developers aspiring to be a 'Data Scientist'
  • Analytics Managers who are leading a team of analysts
  • Business Analysts who want to understand Machine Learning (ML) Techniques
  • Information Architects who want to gain expertise in Predictive Analytics
  • 'R' professionals who wish to work Big Data
  • Analysts wanting to understand Data Science methodologies

 

Course Info.

Lenght
30+hours
Effort
2-3 hours/week
Institution
Open Source
Language
English
Video Script
English

Training Options

Selfpaced Training

299
  • Lifetime access to high-quality self-paced eLearning content curated by industry experts
  • 3 simulation test papers for self-assessment
  • Lab access to practice live during sessions
  • 24x7 learner assistance and support

Live Virtual Classes

499
  • Online Classroom Flexi-Pass
  • Lifetime access 
  • Practice lab and projects with integrated Azure labs
  • Access to Microsoft official content aligned to examination

One on One Training

1100
  • Customized learning delivery model (self-paced and/or instructor-led)
  • Flexible pricing options
  • Enterprise grade learning management system (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support

Exam & Certification

No examination required.

Towards the end of the course, you will be working on a project. on successful completion, Wissenhive certifies you as a 'Data Science Expert' based on the project.

Data Science Course with R

FAQs

If you have a Windows system, you should have:

  • Microsoft Windows 7 or newer (32-bit and 64-bit)
  • Microsoft Server 2008 R2 or newer
  • Intel Pentium 4 or AMD Opteron processor or newer
  • 2 GB memory
  • 1.5 GB minimum free disk space
  • 1366 x 768 screen resolution or higher

If you have a MAC system, you should have:

  • iMac/MacBook computers 2009 or newer
  • OSX 10.10 or newer
  • 5 GB minimum free disk space
  • 1366 x 768 screen resolution or higher

For executing the practicals, you will set-up R programming IDE on your machine, you can:

  • Download RStudio Desktop Open Source License from the Rstudio Official Website for free
  • Or, purchase the licensed Full- version of RStudio Desktop Commercial License

The detailed step by step installation guides will be present in your LMS which will help you to install and set-up the required environment. In case you come across any doubt, the 24*7 support team will promptly assist you.

Data science is an evolutionary step in interdisciplinary fields like the business analysis that incorporate computer science, modelling, statistics and analytics. To take complete benefit of these opportunities, you need a structured training with an updated curriculum as per current industry requirements and best practices.

Besides strong theoretical understanding, you need to work on various real-life projects using different tools from multiple disciplines to gather a data set, process and derive insights from the data set, extract meaningful data from the set, and interpret it for decision-making purposes.

Additionally, you need the advice of an expert who is currently working in the industry tackling real-life data-related challenges.