Given corporate training to many MNC's for Subjects like: Scala, Python, Machine Learning, Deep Learning, Bigdata etc

Data Science With R Training in Pune

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What is Data Science?

Data Science is a new interesting software technology, which is used to apply critical analysis, provide the ability to develop sophisticated models, for massive data sets and drive the business insights. Data Science utilizes the potential and scope of Hadoop, R programming, and machine learning implementation, by making use of Mahout. Data Science training pune and Data Analytics training pune we have Data Interpretation for Business Intelligence.

Syllabus

• What is Data Analytics?
• Types of Data Sets and Data Models
• Understanding of Business Analytics
• Need of Business Analytics
• Types of Business Analytics
• Descriptive Analytics
• Predictive Analytics
• Prescriptive Analytics
• Supply Chain Analytics
• Health Care Analytics
• Marketing Analytics
• Human Resource Analytics
• Data Management and Business Analytics
• Web Analytics and Business Intelligence
• Data Science as a Strategic Asset
• Data Warehousing and OLAP
• Data Visualization using R and Excel
• Data Visualization using Tableau

• Understanding R
• Which Companies Use R?
• Understanding Comprehensive R Archive Network (CRAN)
• How to Install R on Operating Systems?
• How to Install R on Windows from CRAN Website?
• IDEs for R
• R Packages: Installation and Practice
• Understanding R Programming
• Studying Operators in R
• Operators: Arithmetic, Relational, Logical, Assignments
• Statements in R Programming
• Conditional Statements in R
• Break and Next Statement
• If else () Function
• Switch Function
• Scan () Function
• Loops in R
• How to Run an R Script and Batch Script?
• R Functions: Commonly Used and String Functions
• Defining Data Structures in R
• Types of Data Structures
• Vectors and Scalars
• Colon Operator
• Matrices
• Elements: Vector, Matrix, Array
• Understanding Data Frames
• Factors and Lists
• How to Import Files in R?
• How to Import an Excel File?
• How to Import Minitab File?
• Importing Table and CSV Files
• Importing Data from SQL Databases
• How to Export Files from R?

•How to Export Files from R?
• Types of Apply Functions
• Apply () Function: Lapply, Sapply, Tapply
• Vapply () Function, Mapply () Function
• Understanding Dplyr Package
• R Data Structures – Vectors, Factors, Lists, Data Frames, Matrixes and Arrays
• Managing Data with R
• Saving and Loading R Data Structures
• Importing and Saving Data from CSV Files
• Importing Data from SQL Databases
• Exploring the Structure of Data
• Exploring and Understanding Data
• Exploring Numeric Variables
• Understanding Types of Data
• Qualitative and Quantitative Analysis
• Studying Descriptive Statistics
• Exploring Numeric Variables
• Measuring the Central Tendency – The Model
• Measuring Spread – Variance and Standard Deviation
• Visualizing Numeric Variables – Boxplots and Histograms
• Understanding Numeric Data – Uniform and Normal Distributions
• Measuring the Central Tendency – The Mode
• Exploring Relationships between Variables
• Visualizing Relationships – Scatterplots
• Nominal and Ordinal Measurement
• Interval and Ratio Measurement
• Statistical Investigation
• Inferential Statistics
• Probability and Central Limit Theorem
• Exploratory Data Analysis
• Normal Distribution
• Distance Measures
• Euclidean & Manhattan Distance

• Minkowski & Mahalanobis
• Cosine
• Correlation
• PPMC (Pearson Product Moment Coorelation)
Machine Learning Techniques using R
Hypothesis Testing
• Implementing Machine Learning Algorithms on larger Data Sets
with Apache Mahout
• How do Machines Learn?
• Abstraction and Knowledge Representation
• Generalization
• Assessing the Success of Learning
• Steps to apply Machine Learning to your Data
• Choosing a Machine Learning Algorithm
• Thinking about the Input Data
• Thinking about Types of Machine Learning Algorithms
• Matching your Data to an Appropriate Algorithm
• Importance of Hypothesis Testing in Business
• Null and Alternate Hypothesis
• Understanding Types of Errors
• Contingency Table and Decision Making
• Confidence Coefficient
• Upper Tail Test and Test Statistics
• Understanding Parametric Tests
• Z-Test and Z-Test in R
• Chi-Square Test
• Degree of Freedom
• One-Way ANOVA Test
• F-Distribution, F-Ration Test

• Data Preparation for Modelling
• How do Machines Learn?
• Choosing a Machine Learning Algorithm

• Supervised Learning Techniques and Algorithms
• Understanding Process Flow of Supervised Learning Techniques
• K-NN, Naïve Bayes, Support Vector Machines
• Defining Classification
• Understanding Classification and Prediction
• Decision Tree Classifier
• How to Build Decision Trees?
• Basic Algorithm for a Decision Tree
• Decision Trees and Data Mining
• Random Forest Classifier
• Features of Random Forests
• Out of Box Error Estimate and Variable Importance
• Naïve Bayes Classifier Model
• Bayesian Theorem
• Advantages and Disadvantages of Naïve Bayes Classifier Model
• Understanding Support Vector Machines
• What is Geometric Margin SVMs?
• Understanding Linear SVMs
• Machine Learning Techniques Using R
• Machine Learning: Tasks, Features, Models, and Design
• Machine Learning Common Use Case
• Supervised and Unsupervised Learning Techniques
• Clustering
• Similarity Metrics
• Distance Measure Types: Euclidean
• Cosine Measures
• Creating predictive Models
• Classification using Nearest Neighbors
• Studying Clustering
• Clustering and Classification
• Understanding K-means Clustering
• K-means and Pseudo Code
• K-means Clustering using R

• TF-IDF and Cosine Similarity
• Application to Vector Space Model
• What is Hierarchical Clustering?
• Hierarchical Clustering Algorithm
• Understanding Agglomerative Clustering Process
• DBSCAN Clustering
• What is Association Rule Mining?
• Association Rule Strength Measures
• Checking Apriori Algorithms
• Ordering Items
• Understanding Candidate Generation
• Performing Visualization on Associated Rules

• Understanding Neural Networks
• From Biological to Artificial Neurons
• Activation Functions

• What is Regression?
• Model Selection
• Generalized Regression
• Simple Linear Regression
• Multiple Linear Regression
• Correlations
• Correlation between X and Y
• Ridge and Regularized Regression
• LASSO
• Time Series
• Prediction: Time Dependent/Variant Data
• Ordinary Least Square Regression Model
• Dummy Variable Regression Model
• Interaction Regression Model
• Non-Linear Regression Model
• Perform Regression Analysis with Multiple Variables

FAQ

If you miss a lecture, you can attend another session in any other live batch. We have multiple batches running simultaneously.

Yes, we have multiple centers. We are located at Pimple Saudagar, Nal Stop, and Kharadi. You can reach us from every corner of the city.

Yes, we arrange demo sessions for all the courses at all the branches. After attending a demo session, you come to know about the advantages of undergoing training, and about the importance of hands-on tasks.

Our training professionals are highly qualified and have hands-on industry experience.

Yes, the courses available at the ETLhive are a perfect blend of theory and practice. We do arrange Live-Projects so that the trainees get an extensive knowledge about the real-time projects and the allied issues, and consequently develop the ability to tackle real-life scenarios.

Yes, we are into three kinds of training: Customer Training, Corporate Training, and Online Training. The training centers are well-equipped which makes online learning possible, enjoyable and effective. Online training is delivered through the use of Webinars, High Definition Videos, and Audio Capability Servers. We will help you attend the course remotely from your desktop or laptop, with the help of local access.

We make sure we are available for our customers. In case you have any doubts after you complete your course, do not hesitate to contact us. Our support system ensures assistance and we will try to clear all your doubts.

You may attend the next batch in case you are unable to attend the batch you enrolled in. The information about our future batches is always available on our website and on other social media links such as Facebook, Twitter, and Google+.

ETLhive is considered as the leading pioneer in customer, corporate, and online training. Our training professionals impart the best of training experiences with detailed theoretical knowledge and real-time projects, so much so that our students excel in their careers. We provide job assistance in terms of resume preparation and interview etiquettes.

The schedule for all the courses is different. You may check our website or our social media links for latest information. Nevertheless, our support staff will inform you about the schedule of your class via email, SMS, or call.

Yes, we provide various kinds of learning material which will help you master the course. We provide PDFs, PPTs, Recorded Videos, Certification Related PDFs, and Best Practices. We also provide FAQs for Interviews and Sample Resumes.

Yes. We have a wide range of online study material. We provide PDFs, PPTs, Recorded Videos, Certification Related PDFs, and Best Practices. We also provide FAQs for Interviews and Sample Resumes.

You can pay through cash or net banking. We also accept cheques liable to be cleared 24 hours before the first lecture of the batch.

After you complete your course modules, you will have to work on projects. We will provide certificates after evaluating your projects, thereafter you will be considered as certified professionals.

If you have any other query, do not hesitate to consult our counsellors. Feel free to call us at 1800-2000-991/8055020011, or email us on [email protected]

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