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DataScience

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  • Multi Instructor sessions

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DataScience Training

Do you desire to become Data Scientist? Maxsoft, Datascience Training Course will provide you with all the skills in order to successful work as a Hadoop Administrator. This Course includes fundamentals of Hadoop, Hadoop Clusters, HDFS, MapReduce, HBase,BI tool and R languge. The training will make you proficient in working with Hadoop clusters and deploy that knowledge on real world projects to visualize and conceptualize for business.

Who should take this Data Science Training Course?

  • Software professionals, BI professional and Architects
  • IT managers, Support Engineers, QA professionals
  • Students who want to have bright future in data science

What are the prerequisites for taking this Hadoop admin online training Course?

No prerequisites required for taking this training. Having a basic knowledge of Linux and Java can help.

What you will learn in this Hadoop admin Training Course?

  • Learn about Hadoop Architecture and its main components
  • Learn Hadoop installation and configuration
  • Deep dive into Hadoop Distributed File System (HDFS)
  • Understand MapReduce abstraction and its working
  • Troubleshoot cluster issues and recover from Node failures
  • Learn about Hive, Pig, Ooozie, Sqoop and Flume
  • Optimize Hadoop cluster for high performance
  • BI tools
  • Machine learning
  • R-language

Upon completion of this course at Maxsoft, the candidates will be proficient into:

  • Realize the core concepts of Apache Hadoop, HDFS , Hadoop Cluster
  • Identify concepts associated to MapReduce,YARN, HDFS Federation, and Name Node High Availability
  • Grasp the ability to load Data and run applications
  • Know about Performance Tuning
  • Execute Data analytics using HBase Administration, Oozie and Hcatalog/Hive
  • Analyze to secure a deployment and realize Backup and Recovery
  • Clean the data and visualize data using R.
  • Machine learning(Supervised and un-supervised)

Assignments

We will provide you practical coursework and system access after every class to complete before the next class begins. We will offer you with our 24 * 7 support team to assist you in resolving your queries online during the lab hours.

Future Scope and Job opportunities:

Business Analyst/ Data Science etc. are words, which describes a new job opportunity in today’s era. No wonder it’s called the sexiest job of 21st Century. The world has now turned into a digital workspace. We have data all around us and a person who can use this data to provide a better insight is called a data science/ Business analyst. This profile has been suggested as the hottest profile for the next 5-6 decades.

Data science Introduction

  • Data Science motivating examples -- Nate Silver, Netfilx, Money ball, okcupid, LinkedIn,
  • Introduction to Analytics, Types of Analytics,
  • Introduction to Analytics Methodology
  • Analytics Terminology, Analytics Tools
  • Introduction to Big Data
  • Introduction to Machine Learning

R software:

1. Introduction and Overview of R Language

  • Origin of R, Interface of R,R coding Practices
  • R Downloading and Installing R
  • Getting Help on a function
  • Viewing Documentation

2. Data Inputting in R Data Types

  • Data Types, Data Objects, Data Structures
  • Creating a vector and vector operations
  • Sub-setting
  • Writing data
  • Reading tabular data files
  • Reading from csv files
  • Initializing a data frame
  • Selecting data frame cols by position and name
  • Changing directories
  • Re-directing R output

3. Data Manipulation in R

  • Appending data to a vector
  • Combining multiple vectors
  • Merging data frames
  • Data transformation
  • Control structures
  • Nested Loops

4. Splitting

  • Strings and dates
  • Handling NAs and Missing Values
  • Matrices and Arrays
  • The str Function
  • Logical operations
  • Relational operators
  • generating Random Variables
  • Accessing Variables
  • Matrix Multiplication and Inversion
  • Managing Subset of data
  • Character manipulation
  • Data aggregation
  • Subscripting

5. Functions and Programming in R

  • Flow Control: For loop
  • If condition
  • While conditions and repeat loop
  • Debugging tools
  • Concatenation of Data
  • Combining Vars, cbind, rbind
  • sapply, lapply, tapply functions

Basic Statistics in R

Part-I Session 1

  • Descriptive Statistics Introduction to Advanced Data Analytics
  • Statistical inferences for various Business problems
  • Types of Variables, measures of central tendency and dispersion
  • Variable Distributions and Probability Distributions
  • Normal Distribution and Properties
  • Computing basic statistics
  • Comparing means of two samples
  • Testing a correlation for significance
  • Testing a proportion
  • Classical tests (t,z,F)
  • ANOVA
  • Summarizing Data
  • Data Munging Basics

Part-I Session 2

  • Test of Hypothesis Null/Alternative Hypothesis formulation 7
  • One Sample, two sample (Paired and Independent) T/Z Test
  • P Value Interpretation
  • Analysis of Variance (ANOVA)
  • Non Parametric Tests (Chi-Square, Kruskal-Wallis, Mann-Whitney.)

Part-I Session 3

  • Introduction to Correlation - Karl Pearson
  • Spearman Rank Correlation

Advanced Analytics with real world examples (Mini Projects)Part-II Session 1

  • Regression Theory
  • Linear regression
  • Logistic Regression Non Linear Regressions using Link functions
  • Logit Link Function
  • Binomial Propensity Modeling
  • Training-Validation approach

Part-II Session 2

  • Factor Analysis Introduction to Factor Analysis – PCA
  • Reliability Test 4
  • KMO MSA tests, Eigen Value Interpretation
  • Factor Rotation and Extraction

Part-II Session 3

  • Cluster Analysis Introduction to Cluster Techniques
  • Distance Methodologies
  • Hierarchical and Non-Hierarchical Procedures
  • K-Means clustering
  • Wards Method

Time Series AnalysisPart-III Session 1

  • Introduction and Exponential Smoothening Introduction to Time Series Data and

Analysis

  • Decomposition of Time Series
  • Trend and Seasonality detection and forecasting
  • Exponential Smoothing (Single, double and triple)

Part-III Session 2

  • ARIMA Modeling Box - Jenkins Methodology
  • Introduction to Auto Regression and Moving Averages, ACF, PACF

Data Mining : Machine learning with R:Part IV Session 1

  • Introduction to Machine learning and various machine learning techniques
  • Introduction to Data Mining
  • Introduction to Text Mining
  • Text analytic Process
  • Sentiment Analysis

Part IV

  • Statistical Analysis & Data Mining/Machine Learning
  • Cluster Analysis using R-Rattle
  • Association Rule Mining
  • Predictive Modeling using Decision Trees
  • Supervised learning
  • Un- Supervised learning
  • Reinforcement learning
  • Neural Network
  • Support Vector machine

Part IV Session 3

  • Evaluating & Deploying Models Evaluating performance of Model on Training and Validation data
  • ROC, Sensitivity, Specificity, Lift charts, Error Matrix
  • Deploying models using Score options
  • Opening and Saving models using Rattle

Analytics in Excel - 3 days

  • Data Preparation and Data Exploration in Excel
  • Network Analysis using NodeXL

Data Visualization in R

  • Creating a bar chart, dot plot
  • Creating a scatter plot, pie chart
  • Creating a histogram and box plot
  • Other plotting functions
  • Plotting with base graphics
  • Plotting with Lattice graphics
  • Plotting and coloring in R

Tableau with Case studiesSAS E Miner with use casesProject : Financial Project, Health care Project, Retail Project

1. Which Case-Studies will be a part of the Course?
We will assist you to work on a real time project case studies on the topics covered after course completion. Our instructors will assist you in assigning two projects during the course. All these projects will be practical case studies along with corporate training materials, best online training software, and online software training videos which help you to gain experience - become Senior Big Data Hadoop Admin professionals ahead.

2. How will I execute the practicals?
We will assist you to set the desired environment for executing the practicals of our classes. We also offer set –up documents in our LMS as per your need. If you have any doubts, 24*7 support will always be available in order to solve your queries online.

3. What if I miss a class?
There is no possibility of skipping or losing our training sessions. If it happens, you can simply select one of the following options given below:

  • Learn the recorded sessions of the skipped class through your LMS
  • Live batches, access your skipped sessions of any one from the live batches

4. What if I have queries after I complete this course?
We offer 24*7 Support Team all the time for your access. Also, the team will assist you in answering your queries whenever needed i.e. between and after the batch.

5. How soon after Signing up would I get access to the Learning Content?
We will help you to get access to our LMS immediately after your enrolment. Moreover, you will be provided with an absolute record of our earlier training sessions, presentations, PDFs, assignments. You can begin your learning process consequently by accessing our 24*7 support team as well.

6. Is the course material accessible to the students even after the course training is over?
Yes, it is possible. Once your enrolment is done into the respective course category, you can easily access to the course materials, which are available for a period of time.

7. Who is the Instructor?
Our group of instructors is all working experts from the business with 10-13 years of experience associated to different domains. All of them are subject matter experts (SMEs) and are highly trained by Software tekies.com to provide a great learning experience to the candidates successfully.

8. Do you provide placement assistance?
Maxsoft is one of the popular online instructor led and corporate training centre operating successfully. Because of our global presence, number of recruitment firms approaches us for student profiles from time to time. We assist our certified students to prepare their resumes, gain real-time experience and offer assistance for preparing interviews as there is a huge opportunities for Big Data Hadoop Admin Professionals. However, we can’t promise you with placements but we deliver our course carefully and finish the project so that you will attain very good hands on knowledge to work on a live project.

9. I have recently enrolled but I am unable to continue in the same batch. Can I reschedule it to a future date?
Yes, we will provide privileges for you to register at this instant and postpone your classes in future date as well. However, you can access our website to get detailed information about the upcoming batches.

10. Can I enrol now and take LIVE classes after a month or later?
Yes, you can register in the early bird batches first and may connect the classes shortly.

11.Can I get the recorded sessions of a class from some other batches before attending a live class?
Yes, it is possible. We provide recorded sessions assuring that the concepts highlighted in our classes will be absolutely familiar to you when you will join with your batch. Also, we believe that you will reach to a position to ask the right questions and acquire the information about the course as you would have already completed some homework from your end.

12. When are the classes held and when I will do practicals?
We will help you with your live classes to be conducted on Weekends. Also, we provide practical coursework covering each module which you can perform at your own schedule with the assistance of our 24* 7 proficient support group besides live classes. You will experience a real time project at the end of course completion.

13. What are the system requirements for this course?
The entry level system requirements for this course involve:

  • 4GB RAM
  • 10 GB Disk space with dual core CPU

14. How much internet speed is required to attend the LIVE classes?
About 1 Mbps of internet speed is needed to continue the LIVE classes. According to our observation, we have come across some candidates continuing the classes even with a very lesser internet speed as well.

15. What are the payment options?
You can pay online by using your Debit Card, Credit Card, or Net Banking service from the outstanding banks. You can use a CCAvenue Payment Gateway to make the payments. You can pay by PayPal for USD payment. Moreover, you can use our existing EMI options depending on your convenience.

16. What if I have more queries?
We will provide you with support Team who will be available online 24*7 for a specific time period. Also, the Team will assist you in answering the issues between and after the batch.