Data Science with R
- Offered byKnowledgeHut
Data Science with R at KnowledgeHut Overview
Duration | 40 hours |
Start from | Start Now |
Total fee | ₹59,990 |
Mode of learning | Online |
Official Website | Go to Website  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
- Admission Process
Data Science with R at KnowledgeHut Highlights
- Earn a certificate after completion of course
- Fee can be paid in installments
- 6 Real-world Live Projects to Apply Your Knowledge
Data Science with R at KnowledgeHut Course details
Those interested in the field of data science
Those looking for a more robust, structured R learning program
Those wanting to use R for effective analysis of large datasets
Software or Data Engineers interested in quantitative analysis with R
Get acquainted with various analysis and visualization tools such as ggplot and Plotly
Understand the behavior of data; build significant models to understand Statistics Fundamentals
Learn about the various R libraries like Dplyr, Data.table used to manipulate data
Use R libraries and work on data manipulation, data preparation and data explorations
Understand the use of R graphics libraries like ggvis, Plotly, and much more
Get hands-on with ANOVA, Linear Regression using OLS, Logistic Regression using MLE, KNN, Decision Trees
This intensive program covers a wide spectrum of Data Science teaching concepts like exploratory data analysis, statistics fundamentals, hypothesis testing, regression and classification modeling techniques, and machine learning algorithms
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 fields of statistical computation and data science.
You will create R programs that will help discover and interpret relationships in complex information and solve real world problems
You will also learn to create R visualizations that will help analyze and handle large data sets
Class Schedule
Data Science with R at KnowledgeHut Curriculum
1. Intro to Data Science
What is Data Science
Analytics Landscape
Life Cycle of a Data Science Project
Data Science Tools & Technologies
2. Mastering R
Intro to R Programming
Installing and Loading Libraries
Data Structures in R
Control & Loop Statements in R
Functions in R
Loop Functions in R
String Manipulation & Regular Expression in R
Working with Data in R
Data Visualization in R
Case Study
3. Probability & Statistics
Measures of Central Tendency
Measures of Dispersion
Descriptive Statistics
Probability Basics
Marginal Probability
Bayes Theorem
Probability Distributions
Hypothesis Testing
4. Advanced Statistics & Predictive Modeling - I
ANOVA
Linear Regression (OLS)
Case Study: Linear Regression
Principal Component Analysis
Factor Analysis
Case Study: PCA/FA
5. Advanced Statistics & Predictive Modeling - II
Logistic Regression
Case Study: Logistic Regression
K-Nearest Neighbor Algorithm
Case Study: K-Nearest Neighbor Algorithm
Decision Tree
Case Study: Decision Tree
6. Time Series Forecasting
Understand Time Series Data
Visualizing TIme Series Components
Exponential Smoothing
Holt's Model
Holt-Winter's Model
ARIMA
Case Study: Time Series Modeling on Stock Price
7. Capstone Projects
Industry relevant capstone project under experienced industry-expert mentor
Data Science with R at KnowledgeHut Admission Process
Important Dates
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