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    Course Details

    Data Science is a process of extracting knowledge from data. Data science is emerging to meet the challenges of processing large data sets which require versatile skill set and specialized in specific domain. Data scientist analyse the complex problems and ensures rich consistency of data sets by creating visualizations to aid in understanding data. Data science training is designed to teach the techniques of data mining and gain knowledge on the insight of visualization and optimization of data to become a successful Data Scientist.

    Data Science Training Overview

    Our Data Science training programme will be conducted by our well experienced data scientists, who also offer networking opportunities with peers, case studies and deep dives into selected topics. Post attending our Data Science Training programme, our students can upgrade their roles and responsibilities to a data scientist. The Data Science course modules, contain machine learning techniques and methodologies to efficiently analyse big-data using Hadoop and R, also concepts of Sqoop and Flume, write Hadoop MapReduce Jobs, implement Language processing and Apache Mahout compassing the complete Data Science study with real-time project by IT Professional.

    Data Science Training Curriculum

    This module will introduce you to Data Science throwing light on Why data science?, Analysing Big Data, Architecture and methods to solve Big Data issues, Data visualization etc…

    Introduction to Big Data
    Roles played by a Data Scientist
    Analysing Big Data using Hadoop and R
    Different Methodologies used for analysis in Data Science
    The Architecture and Methodologies used to solve the Big Data problems
    Data Acquisition from various sources
    Data preparation
    Data transformation using Map Reduce (RMR)
    Application of Machine Learning Techniques, Data Visualization etc.,
    Problem statement of few data science problems which we shall solve during the course

    This module teaches how to manipulate data and use R for all kinds of data conversion and restructuring processes that are frequently encountered in the initial stages of data analysis  in Data Science Training.

    Understanding vectors in R
    Reading Data
    Combining Data
    Sub-setting data
    Sorting data and some basic data generation functions

    The goal of machine learning is to create a predictive model, that is indistinguishable from a correct model. This module, starts off giving you an overview about machine learning in Data science Training.

    Machine Learning Overview
    ML Common Use Cases and techniques
    Clustering and Similarity Metrics
    Distance Measure Types: Euclidean, Cosine Measures, Creating predictive models

    This module is designed to teach you ‘K’ means clustering, association rule mining and much more..

    Understanding K-Means Clustering in Data Science
    Understanding TF-IDF and Cosine Similarity and their application to Vector Space Model
    Implementing Association rule mining in R.

    The last part of machine learning module of Data Science course, trains on Decision Tree’s, Random forests concept in Data Science.

    Understanding Process flow of Supervised Learning Techniques
    Decision Tree Classifier
    How to build Decision trees
    Random Forest Classifier
    What is Random Forests concept in data science
    Features of Random Forest
    Out of Box Error Estimate and Variable Importance
    Naive Bayes Classifier

    Understand the Hadoop architecture, its commands, SQOOP and other data loading techniques in this module.

    Hadoop Architecture
    Common Hadoop commands
    MapReduce and Data loading techniques (Directly in R and in Hadoop using SQOOP, FLUME, and other data Loading Techniques)
    Removing anomalies from the data

    This module of Data science course, will give good knowledge on how R is integrated with R, the integrated programming environment and writing MapReduce jobs.

    Integrating R with Hadoop using R
    Hadoop and RMR package
    Exploring RHIPE (R Hadoop Integrated Programming Environment)
    Writing MapReduce Jobs in R and executing them on Hadoop

    By the end of this module, you will be able to implement machine learning algorithms with Mahout

    Implementing Machine Learning Algorithms on larger Data Sets with Apache Mahout

    In this module, you will learn how to implement Random Forest Classifier with Parallel Processing Library using R.

    Implementation of different Mahout algorithms
    Random Forest Classifier with parallel processing Library in R

    The aim of the project module is to let you have an idea of what a project is, problem statement, various approaches and solving algorithms.

    Project Discussion
    Problem Statement and Analysis
    Various approaches to solve a Data Science Problem
    Pros and Cons of different approaches and algorithms

    Faqs

    Our trainers have relevant experience in implementing real-time solutions on different queries related to different topics. Mindmajix verifies their technical background and expertise.

    We record each LIVE class session you undergo through and we will share the recordings of each session/class.

    Trainer will provide the Environment/Server Access to the students and we ensure practical real-time experience and training by providing all the utilities required for the in-depth understanding of the course.

    If you are enrolled in classes and/or have paid fees, but want to cancel the registration for certain reason, it can be attained within 48 hours of initial registration. Please make a note that refunds will be processed within 30 days of prior request.

    The Training itself is Real-time Project Oriented.

    Yes. All the training sessions are LIVE Online Streaming using either through WebEx or GoToMeeting, thus promoting one-on-one trainer student Interaction.

    There are some Group discounts available if the participants are more than 2.

    As we are one of the leading providers of Online training, We have customers from USA, UK, Canada, Australia, UAE, Qatar, NZ, Singapore, Malaysia, India and other parts of the world. We are located in USA. Offering Online Training in Cities like

    Minneapolis, Melbourne, Jacksonville, Davidson, Murfreesboro, Auckland, Carlsbad,  San Marcos, Tacoma, Bellevue, Garland, Raleigh-Cary, Fort Lauderdale, Miami, Toronto, Wellington, Gilbert, Tempe, Alexandria, Chandler, Scottsdale, Peoria, Honolulu, Raleigh, Nashville, Plano, Montreal, Calgary, Edmonton, Saint John, Vancouver, Richmond, Mississauga, Saskatoon, Kingston, Kelowna, Hyderabad, Bangalore, Pune, Mumbai, Delhi, Dubai, Doha, Brisbane, Perth etc…

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    Exam Certification

    How to get certified in Data Science?

    The certifications for data science are provided by reputed organizations like SAS, Jigsaw Academy, UCI, Cloudera, Coursera,Harvard Extension School, Microsoft and Columbia University. For passing these certification exams, an in-depth understanding of all the data science concepts is recommended. The learning path and the project Mindmajix comes up with will be exactly in line with the certification programs which enables you to clear data science certification exams with greater ease and secure a job in top multinationals.

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