2 Months Programme

This Internship Category has been intricately designed, keeping in mind the current Industry requirements for fast track learners. Our resilient groundwork nurture young minds and equip them through pure practical methodologies and less theory sessions. In an advancement to that approach, we leverage latest technology, support your Hands-On needs and further, groom you for your betterment. In a short span of 2 months, the student can grasp, apply the learnt concepts through our platform and practise in Real-time project.

Courses

1.     Overview of Analytics and Data Science

2.     Statistics and Exploratory Data Analytics

3.     Data Visualization

4.     Machine Learning - Part I

Linear Regression

Logistic Regression

Support Vector Machine

Clustering

Principal Component Analysis

 Naive Bayes

5.     Machine Learning – Part 2

Model Selection and Performance Evaluation

Advanced Regression

Tree Model

Boosting (optional)

Neural Network (optional)

Time Series

Geospatial Analysis

6.     Live Project

Understanding Business Domain

Design and Develop Analytics

Refine Visualization and Deliver Analytics

After Program, you will learn below Skills:

·        Step-by-Step Introduction to Machine Learning and Data Visualization

·        Expert in Predictive Analytics and Statistics

Job Roles that you may take up:

                         Data Analyst

                         Data Scientist

Tools Utilized  

R/ Python /Clojure and nEX

 

Ideal for fresher who loves Mathematics



1.     Introduction to Data Science

2.     Data Analysis, Data Cleansing and Data Operations

3.     Statistics and Exploratory Data Analytics

4.     Fundamentals of Statistical Tool

5.     Data Visualization

6.     Machine Learning - Part I

 Linear Regression

Logistic Regression

K-Nearest neighbour and Support Vector Machine

Cluster Analysis

Principal Component Analysis

Naive Bayes

7.     Machine Learning – Part 2

Model Selection and Performance Evaluation

Classification and Regression Trees

Neural Network

Time Series and Causality

Text Mining

Social Media Analysis

Sentiment Analysis

Risk Detection and Prediction – Descriptive and Predictive Analytics

Market Basket Analysis

Recommendation Engine

8.     Live Project

Understanding Business Domain

Design and Develop Analytics

Refine Visualization and Deliver Analytics

 

After Program, you will learn below Skills:

·        Step-by-Step Introduction to NLP, Deep Learning, Reinforcement Learning and Graphical Models

·        Expert in Predictive Analytics and Statistics

Job Roles that you may take up:

              Product Analyst

 Machine Learning Engineer

 Data Scientist

Tools Utilized 

R/ Python /Clojure  and nEX

Ideal for Fresher who loves Mathematics and has taken up Data Science Programme 

1.     Fundamentals of Data Warehousing

2.     Data Extraction, Manipulation and Transformation

3.     Data Modelling

4.     Understanding Business Use cases

              Build Insightful Descriptive and Diagnostic Analysis

              Write Functions and Scripts

              Incorporate Narratives in Storytelling    

5.     Build Semantic Layers for Data Quality

6.     Assess and Monitor Data Governance

7.     Bring Analytical Models for Predictive and Prescriptive Analytics

              Regression

              Forecasting

              Classification

              Clustering

After Program, you will learn below Skills:

·        Step-by-Step Introduction to Predictive Modelling and Machine Learning

·        Expert in Business problem solving and Data Visualization

Job Roles that you may take up:

              Business Analyst

               Data Analyst

               Managerial Roles

Tools Utilized 

QLIK/ POWER BI / TABLEAU

Ideal for Fresher who want to create Intuitive Dashboards and make analytic-drive business decisions

Introduction to Data Science

Statistics and Exploratory Data Analytics

Machine Learning

Linear Regression

       Logistic Regression

       K-Nearest neighbour and Support Vector Machine

       Cluster Analysis

       Principal Component Analysis

        Naive Bayes

Deep Learning

         Introduction to Neural Network

         Convolutional Neural Network

         Recurrent Neural Network

         Object Classification

         Linear Model and Stochastic gradient descent

         Model Validation and Overfitting problem

         Multilayer perceptron (MLP)

         Matrix Derivative

Natural Language Processing (NLP)

          Sequential Model

          Perplexity and Probabilities of Sequence Tagging

          Distributional Semantics

          Word and sentence embedding             

 After Program, you will learn below Skills:

·        Step-by-Step Introduction to Image Processing and Recommendation Engine

·        Expert in Machine Learning

Job Roles that you may take up:

              Data Analyst

              Data Scientist

              Machine Learning Engineer

Tools Utilized 

TensorFlow / Keras

Ideal for Fresher who want to pursue career in Image Recognition and Pattern Detection

 

Design and Style Web page using Bootstrap

Setup Web Tools and Manage Web Site

Build Responsive UI design using Angular

          Data Binding

          Angular Router

          Client- Server communication through HTTP Client

           Use of REST API on server side

Hybrid Application Framework

          Develop and Target multiple mobile platforms with Single Codebase

          Access Native Mobile Capabilities from Javascript

React

         React Router and Design Single Page Application

         React Form

         Flux Architecture and Introduce Flux                          

 After Program, you will learn below Skills:

·        Step-by-Step Introduction to Angular Framework, Hybrid Mobile Application and React

·        Expert in Front-End Web Application

Job Roles that you may take up:

              UI / UX Developer

 

Tools Utilized 

Angular JS, React JS and Node.js 

 

Ideal for Fresher who has working knowledge of HTML, CSS and Javascript

 

Introduction to Big Data Business

Use Cases Big Data

    Fundamentals

    Data Abstraction

    Data Structure (Linear and Non-Linear) Algorithm

    Design and Performance Evaluation using MapReduce

Big Data Platform

    Distributed Computing Environment

    Distributed Data Processing using MapReduce , PIG and SPARK

    Data Storage on Cloud DB

Big Data

     ETL

     Data Injection in Big Data using Apache, Sqoop and Flume NoSQL Dastabases (HBase / MongoDB)

Real-time Processing

    Streaming data using Flume and Kafka

Big Data Analytics

    Linear Regression

    Clustering Classification

After Program, you will learn below Skills:

• Step-by-Step Introduction to MapReduce, Data Warehousing and Real-Time Processing

• Expert in Big Data Analytics

Job Roles that you may take up:

Big Data Engineer

Big Data Analyst

 

 

Tools Utilized

PIG, Map Reduce, Spark, Sqoop , Flume, Kafka , HDFS/ MongoDB

Ideal for Fresher who want to pursue Career in Big Data

What will You learn

  • Lectures from Industry Experts and Consultants
  • Open Discussion Forum after every session
  • Get exposure in 1 Real-time project
  • 10+ Case Studies

What do you get

Dedicated Student Training Manger and Live Project Manager

Access to our system , save time and money on configuration

Practical Hands-on From Day 1

Live Project completion and review

Get certified in Job-oriented Skills

Job Placement Assistance with Top Firms

Enroll Now
  • Really loved the sessions.Was able to learn new things.Very supportive mentors.

    Diptojyoti Dutta - Student
  • A good training session happens here that can help a person to gather new experiences and knowledge about new technologies on a trending field. This session is quite encouraging to learn more on the field and achieve a growing platform for their near future.

    Rounak Mukherjee - Student
  • The training programme is Well conceptualized and well explained.It was very good, educative and informative.The training will no doubt aid and improve my skills. The overall training program is very good and enthusiastic.

     

          

    Arijit Chowdhury - Student
  • An excellant programme which helps me to gain a lot of knowledge on new technologies. I am too encouraged from this session to learn more and more on this field and achieve a platform for my near future. 

    Gopal Pal - Student
  • The environment is well enough to learn Business analysis. The study material and the guidance was well enough from the company. I request you to give us an opportunity to work in live project. 

    Anirban Roychowdhuri - Student
  • LiveDataScience provided me a better environment for learning Microsoft Power BI course.The course was good and knowledgeable. The provided study materials was sufficient for learning the course and got proper support and  guidance from the company. 

    Sushanta Das - Student