Training

ABOUT COURSE

The term Data Science refers to the interdisciplinary concept dealing with systems and process to derive knowledge from both structured and unstructured from different forms of data. Data Science uses techniques, theories and methods extracted from various types of sciences like mathematics, information science, computer science, statistics and many others.The Data Science course enables you to understand practical foundations, helping you effectively execute and take up Big Data and other analytics projects. The program covers topics from Big Data to the Data Analytics Life Cycle. Understanding these topics helps in addressing business challenges that leverage Big Data.

Another aspect of this course is that it covers basic as well as advanced analytic methods, and also introduces the participant to Big Data technologies with tools like MapR and Hadoop. Our state-of-the-art-infrastructure allows students to understand the applications of these methods and tools by getting hands-on experience working alongside real-time data scientists. This program has an open approach including a final lab session, which explains various Big Data Analytics challenges by applying the concepts covered during the program with respect to the Data Analytics Life Cycle.

  • The course is designed for anyone who wishes to understand the concepts of Data Science from a Data Scientist’s perspective. Professionals who can benefit from this course include:
  • Managers from any field, as Analytics is the best tool for managers these days
  • Business Analysts and Data Analysts who wish to upscale their Data Analytics skills
  • Database professionals who aspire to venture into the field of Big Data by acquiring analytics skills
  • Fresh graduates who wish to make a career in the field of Big Data or Data Science

The following skill sets and knowledge will enable students to complete the course successfully, and at the same time, reap maximum benefits:

  • Good understanding of basic statistical concepts and a strong quantitative background
  • Knowledge of any scripting languages such as Java, Perl, Python, or R, as most of the modules in the course use R – an open-source statistical tool, and programming language.
  • Knowledge and experience of SQL
    Knowledge of these pre-requisites will enable the participants to understand various advanced tools and methods covered during the program more effectively.
  • Fresh graduates who wish to make a career in the field of Big Data or Data Science

At the end of the course, the participants will be able to:

  • Be a part of a data science team and work on Big Data and various other analytics projects
  • Deploy the Data Analytics Life Cycle for Big Data projects
  • Change the frame of a challenge from a business perspective to analytics
  • Understand which analytics techniques and tools will work in a specific Big Data analysis
  • Create statistical models and understand which insights can lead to actionable results
  • Select appropriate data visualizations, which would help in communicating analytics insights to business sponsors and analytics audience in a clearer manner
  • Use various Big Data tools like Hadoop, MapR, R, In-Database Analytics, and MADLib functions
  • Understand how to leverage advanced analytics to create a competitive advantage, and how the roles of data scientists and BI analysts are different from each other

A course of Data Science with Test Consulting Group(TCG) gives an insight into few of the above mentioned sciences and the respective theories adopted from them along with their connection with Big Data, Relational Data and programming.

  • Understand the fundamentals and basic concepts in the data science domain
  • Build a strong foundation in math and statistics
  • Be equipped with the programming skills
  • Be an expert on the machine learning algorithms that can be used for data analysis
  • Practice what you’ve learnt on real-world problems across industries

Details of courses

Each week will have the following schedule

  • 1 Day : Theory Class : (2 hours + ½ hour break + 2 Hours)
  • 1 Day : Practical Lab : (2 hours + ½ hour break + 2 Hours)

Duration of this course is 2 months.

This course will provide you knowledge on the following topics:

  • Data Science Domain [1 week]
    Applications of data science so far in various industries and our everyday lives
  • Data Overview [2 Weeks]
    Overview of the different types of data and various sources of data.
  • Data Handling Technologies [2 Weeks]
    Learn the techniques used to identify and treat anomalies in data.
  • Data Analysis Techniques [2 Weeks]
    Learn how to explore, understand and discover patterns in your data.
  • Data Presentation Techniques [2 Weeks]
    Overview of visualizations and reporting used to present findings.

Duration of this course is 4 months.

This course will provide you knowledge on the following topics:

Mathematics for Data Scientists [1 month]
Build a strong foundation by learning the core mathematical concepts that data science is built on. Understand the vocabulary, notation, concepts, and algebra rules that all data scientists are familiar with.

  • Set Theory
  • Calculus
  • Linear Algebra
  • Graph Theory
  • Optimization Techniques

Statistics for Data Scientists [1 month]
Learn how data scientists exercise statistical thinking and how statistics plays a central role in data science

  • Experiment and Data Collection
  • Central Tendency
  • Disbursement
  • Multivariate Analysis
  • Probability Basics
  • Random Variables
  • Probability Distribution
  • Probability Mass function
  • Probability Density function
  • Hypothesis Testing and Quality Control

Programming skills for Data scientist [1 month]
Learn to programme in various languages that are the tools data scientist use to query, retrieve and analyse data

  • Basic Programming Concept
  • Data Structure and Algorithm
  • Python
  • R
  • Java
  • Excel
  • RDBMS
  • Distributed Computing Basics

Distributed Programming [1 month]
Learn how Big Data is stored in a distributed environment and how to retrieve and analyse this data

  • Hadoop Overview
  • Map Reduce Concept
  • Hive
  • Pig
  • Spark / PySpark

Duration of this course is 4 months.

This course will provide you knowledge on the following topics:

Machine Learning [2 months]
Understand the techniques and algorithms used in giving computers the ability to

  • learn with data
  • Machine Learning Basics
  • Bayesian Classification
  • Decision Tree
  • Support Vector Machine
  • Linear Discriminant Analysis
  • Bagging / Boosting

Data Mining [2 months]
Learn the process of discovering hidden patterns and insights in datasets

  • Exploratory Data Analysis
  • Dimensionality Reduction
  • Bayesian Network
  • Markov Chain
  • Hidden Markov Model / Timeseries Analysis
  • Neural Network

Putting Theories in Practice (Case Studies) [Pick any two]
Duration for Practical applications of what you have learnt is 2 months…

  • Social Media Analytics
  • Time Series Analysis (Stock Market)
  • Image Processing
  • Music Analysis
  • Project Management
  • Health and Nutrition
  • E-Commerce
  • Real Estate

COURSE FEATURES

Course Duration:

Each course duration will be 40 hrs minimum . Highly interactive, reliable and quality learning sessions of the course are conducted by TCG. For a better learning experience, the courses are divided into distinctive phases and sessions.

Support:

Concerned faculty can be contacted by the students if they are looking for help and assistance with respect to the course and its material. Students can approach their respective faculty to clear their quires either by email, phone or through live chat

Job Assistance:

TCG will help students find job opportunities with the newly acquired skill set. We would pass your resumes through our site after the completion of the course and ensure that the students achieve 100% placements.

Hands on Experience:

Every module shall be followed by a practical experience of lab exercises. At the end of the course, the students will have to build a project on the concepts that were taught to them during the course duration.

FAQ

  • Understand the fundamentals and basic concepts in the data science domain
  • Build a strong foundation in math and statistics
  • Be equipped with the programming skills
  • Be an expert on the machine learning algorithms that can be used for data analysis
  • Practice what you’ve learnt on real-world problems across industries

Our instructors are certified professionals and are Subject Matter Experts in Data Science

Candidates need not worry about losing any training session. They will be able to view the available recorded sessions on the LMS. We also have a technical support team to assist candidates in case they have any query.

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