Overview:

About Datascientist

Data science is a process of extract the knowledge or insight from the data in various forms either structured and unstructured. Field. Data science supports data scientists to use their data and analytical ability to find and interpret rich data sources The Data Scientists.Net Program is a concept brought to life by two brothers Troy and Shane Sadkowsky who see the massive value and clarity that can be brought to the world through the use of Data Science.

Overview of Datascientist training

SBRtrainings one of the best Institute for Data science online training in hyderabad come up with New and innovative teaching methodologies to make the learning process easier.The entire course curriculum of Data science designed to meet industry requirements. Flexibility, availability, and conveniences are the three key aspects of our online training pattern. Our training helps students to learn real time concepts of Data science The learning process in sbrtrainings is very fun and practical.

Datascientist Course objectives:

A part from general topics candidate will be able to handle special topics such as
• In-depth Knowledge in Introduction to R Programming
• R programming concepts
• Data manipulation
• Data import techniques
• Exploratory data analysis
• Big data& hadoop
• Map reducing concepts
• Pig,hive,Sqoop
• In depth knowledge in all data science core concepts

Who should go for this course

• IT professionals
• Data analyst&professionals
• SQL sever managers
• Basic knowledge on coding
• SQL ,python experts • Technical Graduates

Datascientist Course Content:
Getting Started with Github
Introduction to Git
Introduction to Github
Creating a Github Repository
Basic Git Commands
Basic Markdown
Getting Started with R
Overview of R
R data types and Objects
Getting Data In and Out of R
Subsetting R Objects
Dates and Times
Getting Started with R
Control structures
Functions
Scoping rules of R
Coding Standards for R
Dates and times
Getting Started with R Loop Functions
Vectorizing a Function
Debugging
Profiling R Code
Simulation
Data Extraction, Preparation and Manipulation ( R, MYSQL, HDFS, HIVE and SQOOP
Data Extraction
Downloading Files
Reading Local Files
Reading Excel Files
Reading JSON
Reading XML
Reading From WEB
Reading From API
Data Extraction Reading From HDFS
Reading From MYSQL
SQOOP
Reading FROM HIVE
Saving and Transporting Object
Reading Complex Structure
Data Preparation
Subsetting and Sorting
Summarizing Data
Creating New Variable
Regular Expression
Working With Dates
Data Manipulation
Managing DataFrame with dplyr package
Reshaping Data
Merging Data
Descriptive Statistics
Univariate Data and Bivariate Data
Categorical and Numerical Data
Frequency Histogram and Bar Charts
Summarizing Statistical Data
Box Plot, Scatter Plot, Bar Plot, Pie Chart
Probability
Conditional Probability
Bayes Rule
Probability Distribution
Correlation vs Causation
Average
Variance
Outliers
Statistical Distribution
Binomial Distribution
Central Limit Theorem
Normal Distribution
68-95-99.7 % Rule
Relationship Between Binomial and Normal Distribution
Hypothesis Testing
Hypothesis Testing
Case Studies
Inferential Statistics
Testing of Hypothesis
Level of Significance
Comparison Between Sample Mean and Population Mean
z- Test
t- Test
ANOVA (f- Test)
ANCOVA
MANOVA
MANCOVA
Regression and Correlation
Regression
Correlation
CHI-SQUARE
Principal Of Analytic Graph
Introduction to ggvis
Exploratory and Explainatory
Design Principle
Load ggvis and start to explore
Plotting System in R
ggvis - graphics grammar
Lines and Syntax
Properties for Lines
Properties for Points
Display Model Fits
Transformations
ggvis and dplyr
HTML WIDGET
Geo-Spatial Map
Time Series Chart
Network Node
Predictive Models and Machine Learning Algorithm - Supervised Regression
Regression Analysis
Linear Regression
Non- Linear Regression
Polynomial Regression
Curvilinear Regression
Multiple Linear Regression
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Logistic Regression
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Time Series Forecast
Predictive Models and Machine Learning Algorithm - Supervised Classification
Naïve Bayes
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Support Vector Machine
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Random Forest
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
K- Nearest Neighbors
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Classification and Regression Tree (CART)
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Predictive Models and Machine Learning Algorithm - Unsupervised
K Mean Cluster
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Apriori Algorithm
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Case Study : Customer Analytic - Customer Lifetime Value
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance

Text Mining, Natural Language Processing and Social Network Analysis
Natural Language Processing
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Social Network Analysis
Collect Data
Explore and Prepare the data
Train a model on the data
Evaluate Model Performance
Improve Model Performance
Capstone Project
Saving R Script
Scheduling R Script

FAQ

1. How does the Online training work and Where do I go to access the online training?
All of our online courses are live instructor-led online courses .Course training is conducted through high-quality online technologies like webex,go to meeting.after registration of the course,access details and link will be given to the students.
2.how much internet speed is required to access online course?
1 mb internet speed is enough To access the online live classes.most of the students are access online training with low internet speed
3.Can I get recorded sessions as a material ?
Yes.we will provide all recorded session which you have done in previous classes on live session .complete practical guide and recorded sessions will be given with material.
4.Can I interact with course instructors?
Yes you can interact with instructors via phone or email to clarify you regarding subject also we provide 24/7 live support to our students.
5. what happen if I miss my training classes?
If any student missed any class.we will provide recorded session as a backup session and if you have any doubts regarding missed session our instructors will clarify on the spot.
6.will I get job assistance?
Yes we will provide job assistance for our students after completion of your course our instructors and career counselors will guide you till the student got placed .
7.is there any discount and offers I can avail?
We will not consider it is a business hence We provide all courses at reasonable prices .you can compare with others.even though our courses are very affordable we will some give discounts on selected courses.
8.who are the trainers?
We have 10+experience ,high qualified and certified trainers with industry expert.they are very knowledgeable in their core domains.
9.can I attend a Demo session?
Yes you can attend our demo session after you enroll the course completely it is free of cost and if you miss the demo we will provide prerecorded demo sessions recorded by our experts our experts
10.what are the payment options?
You can pay by credit card,debit card and net banking from all leading banks,for USD payments,you can pay by PayPal.
11.what if I have more queries?
You can give us a call at +91 9494347041 or email at contact@sbrtrainings.com

Online Datascientist Demo Training

Datascientist Course Duration

Online Training
It is a 35 to 40 Hours program and extends up to 2hrs each Day.
Corporate Training
It is a 6 days program and extends up to 8hrs each.
Classroom Training
Private Classroom arranged on request and minimum attendies for batch is 4.