What is Data Science?

What does Data Science involve?

Era of Data Science

Business Intelligence vs Data Science

Life cycle of Data Science

Tools of Data Science

Introduction to Big Data and Hadoop

Introduction to R

Introduction to Spark

Introduction to Machine Learning

What is Statistical Inference?

Terminologies of Statistics

Measures of Centers

Measures of Spread

Probability

Normal Distribution

Binary Distribution

Data Analysis Pipeline

What is Data Extraction

Types of Data

Raw and Processed Data

Data Wrangling

Exploratory Data Analysis

Visualization of Data

Loading different types of dataset in R

Arranging the data

Plotting the graphs

What is Machine Learning?

Machine Learning Use-Cases

Machine Learning Process Flow

Machine Learning Categories

Supervised Learning algorithm: Linear Regression and Logistic Regression

Implementing Linear Regression model in R

Implementing Logistic Regression model in R

What are classification and its use cases?

What is Decision Tree?

Algorithm for Decision Tree Induction

Creating a Perfect Decision Tree

Confusion Matrix

What is Random Forest?

What is Navies Bayes?

Support Vector Machine: Classification

Implementing Decision Tree model in R

Implementing Linear Random Forest in R

Implementing Navies Bayes model in R

Implementing Support Vector Machine in R

What is Clustering & its use cases

What is K-means Clustering?

What is C-means Clustering?

What is Canopy Clustering?

What is Hierarchical Clustering?

Implementing K-means Clustering in R

Implementing C-means Clustering in R

Implementing Hierarchical Clustering in R

What is Association Rules & its use cases?

What is Recommendation Engine & it’s working?

Types of Recommendations

User-Based Recommendation

Item-Based Recommendation

Difference: User-Based and Item-Based Recommendation

Recommendation use cases

Implementing Association Rules in R

Building a Recommendation Engine in R

The concepts of text-mining

Use cases

Text Mining Algorithms

Quantifying text

TF-IDF

Beyond TF-IDF

Implementing Bag of Words approach in R

Implementing Sentiment Analysis on Twitter Data using R

What is Time Series data?

Time Series variables

Different components of Time Series data

Visualize the data to identify Time Series Components

Implement ARIMA model for forecasting

Exponential smoothing models

Identifying different time series scenario based on which different Exponential Smoothing model can be applied

Implement respective ETS model for forecasting

Visualizing and formatting Time Series data

Plotting decomposed Time Series data plot

Applying ARIMA and ETS model for Time Series Forecasting

Forecasting for given Time period

Reinforced Learning

Reinforcement learning Process Flow

Reinforced Learning Use cases

Deep Learning

Biological Neural Networks

Understand Artificial Neural Networks

Building an Artificial Neural Network

How ANN works

Important Terminologies of ANN’s

Data Science Certification Training is designed by industry experts to make you a Certified Data Scientist. The Data Science course offers:

In-depth knowledge of Data Science Life Cycle and Machine Learning Algorithms

Comprehensive knowledge of various tools and techniques for Data Transformation

The capability to perform Text Mining and Sentimental analyses on text data and gain an insight into Data Visualization and Optimization techniques

The exposure to many real-life industry-based projects which will be executed in RStudio

Projects which are diverse in nature covering media, healthcare, social media, aviation and HR

Rigorous involvement of an SME throughout the Data Science Training to learn industry standards and best practices

In-depth knowledge of Data Science Life Cycle and Machine Learning Algorithms

Comprehensive knowledge of various tools and techniques for Data Transformation

The capability to perform Text Mining and Sentimental analyses on text data and gain an insight into Data Visualization and Optimization techniques

The exposure to many real-life industry-based projects which will be executed in RStudio

Projects which are diverse in nature covering media, healthcare, social media, aviation and HR

Rigorous involvement of an SME throughout the Data Science Training to learn industry standards and best practices

Data science is an evolutionary step in interdisciplinary fields like the business analysis that incorporate computer science, modelling, statistics and analytics. To take complete benefit of these opportunities, you need a structured training with an updated curriculum as per current industry requirements and best practices.

Besides strong theoretical understanding, you need to work on various real-life projects using different tools from multiple disciplines to gather a data set, process and derive insights from the data set, extract meaningful data from the set, and interpret it for decision-making purposes.

Additionally, you need the advice of an expert who is currently working in the industry tackling real-life data-related challenges.

Data Science Training will help you become a Data Science Expert. It will hone your skills by helping you to understand and analyze actual phenomena with data and provide the required hands-on experience for solving real-time industry-based projects.

During this Data Science course, you will be trained by our expert instructors to:Gain insight into the 'Roles' played by a Data Scientist

Analyze several types of data using R

Describe the Data Science Life Cycle

Work with different data formats like XML, CSV, etc.

Learn tools and techniques for Data Transformation

Discuss Data Mining techniques and their implementation

Analyze data using Machine Learning algorithms in R

Explain Time Series and it’s related concepts

Perform Text Mining and Sentimental analyses on text data

Gain insight into Data Visualization and Optimization techniques

Understand the concepts of Deep Learning

The market for Data Analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Our Data Science Training helps you to grab this opportunity and accelerate your career by applying the techniques on different types of Data. It is best suited for:

Developers aspiring to be a 'Data Scientist'

Analytics Managers who are leading a team of analysts

Business Analysts who want to understand Machine Learning (ML) Techniques

Information Architects who want to gain expertise in Predictive Analytics

'R' professionals who wish to work Big Data

Analysts wanting to understand Data Science methodologies

Developers aspiring to be a 'Data Scientist'

Analytics Managers who are leading a team of analysts

Business Analysts who want to understand Machine Learning (ML) Techniques

Information Architects who want to gain expertise in Predictive Analytics

'R' professionals who wish to work Big Data

Analysts wanting to understand Data Science methodologies