Data Science training pune and Data Analytics training pune

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.

Program Highlights

IBM Certification

Our program comes with globally recognized IBM certifications at both course and program levels to showcase your knowledge and skills in Data Science. 

Comprehensive Courseware

This intensive curriculum is paced with a unique blend of instructor-led classes, self-paced courses, and hands-on labs to ensure a thorough understanding of each subject.

Hands-on Approach

The program comes with frequent assessments and project work for each course in the learning path and two capstone projects to make you a better data scientist.

Expert Instructors

Having worked for corporations such as Accenture, Amadeus, Syntel, Nielsen and Cognizant, our hand-picked instructors come with a large range of experience, technical expertise and a clear vision of the industry's needs. 

Weekend Online Mentorship Sessions

30 live online mentorship sessions assisted by recorded content, webinars and hackathons. 

Program Support

Our subject matter experts with industry-experience and technical know-how will be extremely happy to guide you through your assignments and project work and are always ready to help you with any questions you may have through your learning journey.

Learning Objective

Data Scientist is one of the hottest professions of the 21st century. As per Forbes, IBM has predicted a rise in demand for Data Scientist by 28% by the year 2020. This course is a combination of forms of learning designed to help a professional gain the required skills and reinforce them through industry-based projects and capstone projects.

The program is aligned with the following learning objectives:
• Gain knowledge about the statistics and programming involved in Data Science.
• Acquire a deep understanding of data structure and data manipulation.
• Learn to perform scientific and technical computing by using Scipy (including Optimize, IO, Statistics, and Weave)
• Master mathematical computing using Numpy and Scikit-Learn packages.
• Know the ins and outs of the different components Hadoop and Spark ecosystem are composed of.
• Learn the difference between RDBMS and HBase, and work with HBase's architecture and data storage system.
• Use Tableau to analyze data and build interactive dashboards, create intriguing visualizations and stories.

  1. Introduction to Data Science
  2. Statistical Methods for Decision Making
  3. Marketing and CRM
  4. Business Finance
  1. Optimization Techniques
  2. Advance Statistics
  3. Data Mining
  4. Predictive Modeling
  5. Time Series Forecasting
  6. Machine Learning
  1. Marketing and Retail Analytics
  2. Web & Social Media Analytics
  3. Finance & Risk Analytics
  4. Supply Chain & Logistics Analytics
  1. Python and R
  2. Tableau
  3. SAS (Online)

Program Syllabus

Data Science Basics
Introduction to Data Science
Statistics Essentials
Data Science with Python
Data Science Overview
Data Analytics Overview
Statistical Analysis and Business Applications
Python Environment Setup and Essentials
Mathematical Computing with Python (NumPy)
Scientific computing with Python (SciPy)
Data Manipulation with Pandas
Machine Learning with Scikit–Learn
Natural Language Processing with Scikit Learn
Data Visualization in Python using matplotlib
Web Scraping with BeautifulSoup
Python integration with Hadoop MapReduce and Spark
Machine Learning
Introduction to Artificial Intelligence and Machine Learning
Data Wrangling and Manipulation
Supervised Learning
Feature Engineering
Supervised Learning
Unsupervised Learning
Time Series Modelling
Ensemble Learning
Recommender Systems
Text Mining
Data Science with R
Introduction to Business Analytics
Introduction to R Programming
Data Structures
Data Visualization
Statistics for Data Science I
Statistics for Data Science II
Regression Analysis
Big Data: Hadoop & Spark
Introduction to Big Data and Hadoop Ecosystem
HDFS and Hadoop Architecture
MapReduce and Sqoop
Basics of Impala and Hive
Working with Hive and Impala
Type of Data Formats
Advanced HIVE concept and Data File Partitioning
Apache Flume and HBase
Apache Pig
Basics of Apache Spark
RDDs in Spark
Implementation of Spark Applications
Spark Parallel Processing
Spark RDD Optimization Techniques
Spark Algorithm
Spark SQL
Tableau Desktop
Getting started with Tableau
Working with Tableau
Deep diving with Data and Connections
Creating Charts
Adding calculations to your workbook
Mapping data in Tableau
Dashboards and Stories
Visualizations for an Audience