Total: 240 Hrs	Instructional: 140 Hrs	Project: 60 Hrs
Assignments: 40 Hrs	2 hrs/per day	English

Hours

Total:
268 Hrs

Instructor

Instructional:
140 Hrs

Project

Project:
60 Hrs

Assignments

Assignments:
60 Hrs

Employability Skills

Employability Skills:
20 Hr

Hours

2 hrs/per day

Language

English

Course Overview

Today, we live in a rapidly evolving globalised era in which the main question is the in-demand status of data science. Indeed, we have arrived at a point where every business must now thrive and survive on the most powerful resource: data. Yes, data has emerged as the new global currency, with future decisions reliant entirely on its metrics. Also, huge investments are made today to drive innovation in data. It is estimated that by 2026, India alone will have 11 million job openings in data science. With increased opportunities, now is the time to become an industry-ready data professional with data-driven skills.

This program will help you build a solid foundation in business decision-making with the help of in-demand data science tools and techniques like Hadoop, Spark, BigML, MongoDB and Tableau, to name a few. With our industry-recognized certificate, you will face no challenges in entering top companies. Enrol right away and embrace the goodness of data science with our in-demand professional course.

Program Fee ₹94900

Schedule on demand

Learning Outcome

Upon completing the course, you become well-versed in the following concepts:

Grasping the basics of Data Science life cycle and understanding Github, R and Cloud technologies
Implementing partitioning, bucketing and indexing in Hive, along with learning how to optimize the Hadoop ecosystem

Performing Data scrapping and Data Processing using PIG and Spark
Getting started with Deep Learning in Cognitive analysis

Syllabus

Module 01 Python for Data Science and Advanced Data Analytics

Understanding of Distribution theorems
Concept of Structured and Unstructured data
Clustering methods and Its implementations
TensorFlow, Keras Libraries for numerical computations
Python Libraries used in Data science and analytics process such as NumPy, Panda, SciKit many more.

Hands-On Assignments - 10 Hours

Module 02 Machine Learning with Python

Introduction to Machine Learning(existing)
Classification algorithm (k-NN, naive Bayes) techniques(existing)
Unsupervised learning algorithm(existing)
Regression algorithm(existing)
Understand The Difference Between Machine Learning & Statistical Data Analysis
machine learning algorithms to predict share prices in stock exchange,detedtion of cancer cells and many more
Boosting and Bagging methods

Hands-On Assignments - 10 Hours

Module 03 Course on Artificial Intelligence

Introduction to Artificial Intelligence
Learning basic statistics and probability theory
Introduction to Python Programming, Tensor flow
Introduction to machine learning, Supervised algorithm for AI problem
Supervised algorithm for AI problem, Decision Tree
Introduction to OPEN-CV, Library and packages to use for image and video processing, Concept of image segmentation in AI
Introduction to NLP(nltk), Text mining using NLP
Text mining processes (tokenizer, stemming, lemmatization, pos, syntax, chunking etc)
Understanding various components of Neural Networks
Keras, Theano, Tensor Flow - Installation, Introduction to Keras, Theano, Tensor Flow.
K-means clustering, Case Study

Hands-On Assignments - 10 Hours

Module 04 Course on Hadoop and Spark

Fundamentals of Hadoop and the ecosystem around it
Working on HDFS, MapReduce, Hive, PIG, and more
Working alongside Avro Data formats
Understanding Spark, Spark SQL, Data frame and other Spark writing applications
Processing RDD in Apache Spark and real time data

Hands-On Assignments - 10 Hours

Module 05 Data Science using R

Introduction to R Programming
Interpret Dataset with Packages
Fundamentals of Statistics & Probability
Data Visualization
Data Distribution & Correlation
Classification - KNN, Naïve Bayes
Decision Tree, Random Forest
Text Mining, WordCloud
Forecasting / Time Series

Hands-On Assignments - 10 Hours

Module 06 Mastering in MongoDB

Mastering MongoDB-based application development
Design MongoDB database from start to finish
Knowing when and where to use MongoDB in your application development
Spot key features and advantages of NoSQL database MongoDB over RDBMS databases
Differentiate between RDBMS and NoSQL databases
Building and running applications

Hands-On Assignments - 10 Hours

Module 07 Advanced Data Visualization with Tableau

Visual Analytics
Data Visualization
Tableau Prep Builder tool
Tableau UI components
Geographic Visualizations in Tableau
Building Dashboards and Stories within Tableau

Hands-On Assignments - 10 Hours

Guided Projects

Creating one dimensional Numpy Array

10 Hrs

Creating two dimensional Numpy Array

10 Hrs

Project on joining and data extract using Tableau

10 Hrs

Performing data analysis on hospital domain in SQL

10 Hrs

Project on Data filtering the Super store data

10 Hrs

Placements and Internship

Digital Marketing
Chennai
Data Scientist / Data Analyst
Chennai
Full Stack developer - Microsoft Stack
Chennai
Full Stack developer - Open Source
Chennai
Software Engineer
Bangalore
Full Stack Developer
Chennai
Trainee Software Developer
Mumbai

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