Software Training Institute in Chennai with 100% Placements – SLA Institute

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Data Science with R Course in Chennai

(7601)
Live Online & Classroom Training

Our Data Science with R Training in Chennai will make students learn some of the most highly regarded concepts in Data Science with R such as – Package Management, Data types, Subsetting, Data Visualization, Logical Regression  etc. This curriculum will surely make students experts in Data Science with R Course in a shorter span of time. Our Data Science with R Course with 100% placement support is curated with the help of leading professionals from the IT industry, which makes our Data Science with R Course up-to-date in accordance to the latest trends.

Our SLA Institute is guaranteed to place you in a high-paying Data Analyst job with help of our experienced placement officers. SLA Institute’s Course Syllabus for Data Science with R covers all topics that are guaranteed to give you a complete understanding of Data Science with R Course.

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Upcoming Batches

Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
July 2024
Week days
(Mon-Fri)
Online/Offline

2 Hours Real Time Interactive Technical Training 

1 Hour Aptitude 

1 Hour Communication & Soft Skills

(Suitable for Fresh Jobseekers / Non IT to IT transition)

Course Fee
July 2024
Week ends
(Sat-Sun)
Online/Offline

4 Hours Real Time Interactive Technical Training

(Suitable for working IT Professionals)

Course Fee

Save up to 20% in your Course Fee on our Job Seeker Course Series

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Placement

100% Assistance

Learning

Job-Centered Approach

Timings

Convenient Hrs

Mode

Online & Classroom

Certification

Industry-Accredited

This Course Includes

  • FREE Demo Class
  • 0% EMI Loan Facilities
  • FREE Softskill & Placement Training
  • Tie up with more than 500+ MNCs & Medium Level Companies
  • 100% FREE Placement Assistance
  • Course Completion Certificate
  • Training with Real Time Projects
  • Industry-Based Coaching By MNC IT Professionals
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Expected Criteria for Assured Placement

The following criteria help the placement team guide the candidates to get placed immediately after the course completion through SLA Institute.

  • 80% of coursework completion helps us arrange interviews in required companies.
  • 2 or 3 projects to be done for the selected course to ace the technical round effectively.
  • Ensure attending the placement training right from the first day of the selected course.
  • Practice well with resume building, soft skill, aptitude skill, and profile strengthening.
  • Utilize the internship training program at SLA for the complete technical skills.
  • Collect the course completion certificate and update the copy to the placement team.
  • Ensure your performance indicator meets the expectation of top companies.
  • Always be ready with the updated resume that includes project details done at SLA.
  • Enjoy unlimited interview arrangements along with internal mock interviews.
Have Queries? Ask our Experts

+91 88707 67784

SLA's Distinctive Placement Approach

1

Tech Courses

2

Expert Mentors

3

Assignments & Projects

4

Grooming sessions

5

Mock Interviews

6

Placements

Objectives of Data Science with R Course in Chennai

The primary objective of our Data Science with R Course in Chennai is to make sure that students grasp the concept of Data Science with R completely. The topics in our Data Science with R Course curriculum covers the complete range of concepts in Data Science with R. So, the following section will explore the concepts taught in Data Science with R at SLA Institute:

  • The syllabus begins with basic concepts like – Overview of R Programming, Downloading and installing, Help of Function, Viewing documentation etc. 
  • The syllabus then moves onto mid-level topics like – Computing Basic Statistics, Comparing means of two samples, Testing a proportion, Data Munging Basics etc.
  • The syllabus then finally goes to an advanced level of topics which ranges from Logical Regression to Hierarchical Clustering PCA for Dimensionality Reduction etc.

Future Scopes for the Data Science with R Course in Chennai

The below section will explore the scopes available in the future for the Data Science with R Course in Chennai:

  • Data Visualization: R is celebrated for its powerful data visualization capabilities through popular packages like ggplot2, plotly, and shiny. Proficiency in R enables data scientists to craft impactful visualizations that effectively communicate insights to stakeholders.
  • Predictive Analytics: R provides a powerful toolkit for developing predictive models, encompassing regression analysis, decision trees, random forests, and advanced techniques such as neural networks and deep learning.
  • Time Series Analysis: R excels in analyzing and forecasting time series data, essential in industries such as finance (for stock market predictions), healthcare (for patient data analysis), and retail (for sales forecasting).
  • High-paying Job: Learning Data Science with R will lead to fruitful and high-paying careers. The Data Analyst Salary in Chennai for freshers and experienced usually ranges from ₹4-20 lakhs annually respectively.

Prerequisites for learning Data Science with R Course in Chennai

SLA Institute does not demand any prerequisites for any course at all. SLA Institute has courses that cover everything from the fundamentals to advanced topics so whether the candidate is a beginner or an expert they will all be accommodated and taught equally in SLA Institute. However having a fundamental understanding of these concepts below will help you understand the Data Science with R better, However it is completely optional:

  • Data Manipulation and Analysis: Experience in tasks such as sorting, filtering, and aggregating datasets enhances one’s ability to manipulate data effectively. Understanding basic data structures (e.g., arrays, lists, data frames) and operations on them is advantageous.
  • Understanding Data Visualization: While not mandatory, familiarity with fundamental data visualization principles aids in comprehending how R’s visualization packages function. This includes knowledge of various plot types (e.g., scatter plots, histograms, bar charts) and principles of effective data representation.
  • Database Skills and SQL Knowledge: Familiarity with extracting and managing data from databases using SQL is valuable, particularly for handling large datasets or integrating R with database systems.
  • Familiarity with Machine Learning Concepts: Basic knowledge of machine learning concepts such as supervised learning, unsupervised learning, and evaluation metrics can be beneficial for those interested in predictive modeling using R.

Our Data Science with R Course in Chennai is ideal to:

  • Students eager to excel in Data Science with R
  • Professionals considering transitioning to Data Science with R careers
  • IT professionals aspiring to enhance their Data Science with R skills
  • Data Scientist enthusiastic about expanding their expertise
  • Individuals seeking opportunities in Data Science with R field.

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Job Profile in Data Science with R Course in Chennai

After completing the Data Science with R Course in Chennai in SLA Institute, students will be placed in a high-paying job on the basis of their skills and qualification. Therefore, here students will explore the various job profiles available for Data Science with R Course:

  • Data Analyst: Gather and interpret data, perform EDA, and create visualizations using R. Familiarity with SQL for data querying is beneficial.
  • Business Analyst: Use R for data analysis, statistical modeling, and creating reports to drive business decisions and process improvements.
  • Research Analyst: Conduct research and analysis using R for data processing, statistical testing, and presenting insights for academic or industry studies.
  • Machine Learning Engineer: Our Data Science with R Course will transform students into successful Machine Learning Engineers who will develop and deploy machine learning models in R for solving complex problems like recommendation systems or predictive analytics.
  • Statistical Analyst: Our Data Science with R Course will make students into Statistical Analyst who will focus on statistical analysis using R for insights and decision support across various domains.
  • Quantitative Analyst: Our Data Science with R Course will make students into expert Quantitative Analysts who will apply R for financial modeling, time series analysis, and risk assessment in quantitative finance roles.
  • Marketing Analyst: SLA Institute will give students enough resources that will turn them into successful Marketing Analysts who will utilize R for data mining, segmentation, and predictive modeling to optimize marketing strategies based on customer insights.
  • Healthcare Data Analyst: The trainers in SLA Institute will provide students with enough training that it will make them into productive healthcare data analysts who will  analyze healthcare data using R for improving patient outcomes, operational efficiency, and epidemiological studies.
  • Consultant: SLA Institute will make students into expert Consultants who will provide data-driven insights and solutions across industries using R for analysis, visualization, and modeling.

Data Science with R Course Syllabus

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SLA Institute’s Data Science with R Course Syllabus comes with 100% placement support so students will be guaranteed a placement in an esteemed organization. In addition to that the Data Science with R Course Syllabus is also carefully curated with the help of leading professionals and experts from the IT industry with so many hours invested in it. So, everything that our students learn in the Data Science with R course is fully up-to-date to the current trends in the IT industry, which increases their chances of getting placed.

Introduction to Data Science
  • What is Data Science?
  • What is Machine Learning?
  • What is Deep Learning?
  • What is AI?
  • Data Analytics & it’s types
Introduction to R
  • What is R?
  • Why R?
  • Installing R
  • R environment
  • How to get help in R
  • R Studio Overview
R Basics
  • Environment setup
  • Data Types
  • Variables Vectors
  • Lists
  • Matrix
  • Array
  • Factors
  • Data Frames
  • Loops
  • Packages
  • Functions
  • In-Built Data sets
R Packages
  • DMwR
  • Dplyr/plyr
  • Caret
  • Lubridate
  • E1071
  • Cluster/FPC
  • Data.table
  • Stats/utils
  • ggplot/ggplot2
  • Glmnet
Importing Data
  • Reading CSV files
  • Saving in Python data
  • Loading Python data objects
  • Writing data to CSV file
Manipulating Data
  • Selecting rows/observations
  • Rounding Number
  • Selecting columns/fields
  • Merging data
  • Data aggregation
  • Data munging techniques
Statistics Basics
  • Central Tendency
    • Mean
    • Median
    • Mode
    • Skewness
    • Normal Distribution
Statistics Basics
  • What does it mean by probability?
  • Types of Probability
  • ODDS Ratio?
  • Standard Deviation
    • Data deviation & distribution
    • Variance
  • Bias variance Tradeoff
    • Underfitting
    • Overfitting
  • Distance metrics
    • Euclidean Distance
    • Manhattan Distance
  • Outlier analysis
    • What is an Outlier?
    • Inter Quartile Range
    • Box & whisker plot
    • Upper Whisker
    • Lower Whisker
    • Scatter plot
    • Cook’s Distance
  • Missing Value treatments
    • What is an NA?
    • Central Imputation
    • KNN imputation
    • Dummification
  • Correlation
    • Pearson correlation
    • Positive & Negative correlation
    • Error Metrics
    • Classification
      • Confusion Matrix
      • Precision
      • Recall
      • Specificity
      • F1 Score
    • Regression
      • MSE
      • RMSE
      • MAPE
    Machine Learning

    Supervised Learning

    • Linear Regression
      • Linear Equation
      • Slope
      • Intercept
      • R square value
    • Logistic regression
      • ODDS ratio
      • Probability of success
      • Probability of failure
      • ROC curve
      • Bias Variance Tradeoff
    Unsupervised Learning
    • K-Means
    • K-Means ++
    • Hierarchical Clustering
    Machine Learning using R
    • Linear Regression
    • Logistic Regression
    • K-Means
    • K-Means++
    • Hierarchical Clustering – Agglomerative
    • CART
    • 5.0
    • Random forest
    • Naïve Bayes

    Want to learn with a personalized course curriculum?

    Project Practices on Data Science with R Training

    Project 1Interactive Dashboard Development with Shiny

    Create interactive dashboards using Shiny in R to visualize and explore datasets. Include features like filters, sliders, and dropdowns for dynamic data exploration.

    Project 2Market Basket Analysis

    Market Basket Analysis: Analyze transactional data (e.g., retail sales) to discover patterns and association rules using R’s arules package. Provide insights and recommendations for product bundling or marketing strategies.

    Project 3Healthcare Analytics

    Predicting Diabetes Onset: Predict the likelihood of diabetes onset using healthcare datasets with logistic regression or decision trees in R. Evaluate model accuracy and identify key predictive factors.

    Project 4Social Media Analytics

    Analyze social media data (e.g., Twitter, Facebook) to monitor trends or sentiment related to specific topics using R. Conduct network analysis or sentiment analysis to gauge public opinion. 

    The Placement Process at SLA Institute

    • To Foster the employability skills among the students
    • Making the students future-ready
    • Career counseling as and when needed
    • Provide equal chances to all students
    • Providing placement help even after completing the course

    Data Science with R Course FAQ

    How do I handle missing data in R?

    Missing data is common and can impact analysis. In R, use is.na() to identify missing values, na.omit() to remove rows with missing data, and na.rm = TRUE in functions like mean() or sum() to exclude missing values from calculations.

    What are some popular packages for data visualization in R?

    R offers several powerful visualization packages:

    • ggplot2: Versatile and elegant for creating a wide range of plots.
    • plotly: Ideal for interactive web-based visualizations.
    • lattice: Useful for multi-panel graphics.
    • ggvis: Provides interactive grammar of graphics using Vega.
    • shiny: Framework for building interactive web dashboards.
    How can I perform feature selection in R for machine learning?

    Feature selection techniques in R include:

    • Filter methods: Such as correlation coefficients and chi-square tests.
    • Wrapper methods: Like recursive feature elimination.
    • Embedded methods: Such as Lasso regression.
    • Packages like caret and glmnet provide functions and tools for feature selection and regularization.
    What is the difference between factor and character data types in R?
    • Character: Stores textual data (e.g., names) as strings.
    • Factor: Represents categorical variables with predefined levels. Factors are used in statistical analyses to maintain categorical semantics and define possible values.
    Does SLA Institute give students EMI options?

    Yes, SLA does indeed give students EMI options with 0% interest.

    What is the infrastructure of SLA Institute?

    SLA Institute is equipped with Smart Computers and Television technologies with active internet that will facilitate a good learning experience both online and offline.

    What is the scope of Data Science with R Course?

    Learning Data Science with R presents strong career prospects due to high demand across industries, its versatile capabilities in statistical analysis and machine learning, robust community support, wide-ranging industry applications, and ability to manage both small and large datasets effectively.

    What job role is best after completing Data Science with R Course?

    Almost all the roles associated with Data Science with R Course will lead to a great career.

    On Average Students Rated The Data Science with R Course 4.70/5.0
    (7601)

    Data Science with R Course is a very good course to deal with data science with R programming skills. The trainers explain topics excellently and they give problems to work out. It was very interesting and easy to learn by doing approach at SLA. The placement team helped in obtaining high salaried jobs in top companies through their training and interview arrangements. I recommend SLA for the candidates who are looking for a great career change.

    Madhu Priya

    It was excellent data science with the R course at SLA. Freshers and working professionals can get benefited from this course as they have a customized syllabus. It helped me gain the career-building skills required for companies. This is the best place to gain specialization in our desired area as they have skilled and experienced trainers to offer the course. The placement support is also very supportive. Overall SLA is a good place to learn and upgrade our skills.

    Ram Prabhu

    I am very much satisfied by reviewing the course syllabus of the Data Science and R Course in Chennai. It was well-planned and well-presented by trainers who are having real-time field experience. I was having little knowledge of R in the beginning. Now I have required industry knowledge to work with R for data science and I can create visualizations effectively through their course. Thanks to the placement team and I thank SLA Institute for providing me with such a good platform

    Premji
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