Data Science with Spark(Big Data - Hadoop) Training lets you gain expertise in Machine Learning Algorithms like K-Means

Clustering, Decision Trees, Random Forest, and Naive Bayes using Spark(Big Data - Hadoop). Data Science Training

encompasses a conceptual understanding of Statistics, Time Series, Text Mining and an introduction

to Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases on

Media, Healthcare, Social Media, Aviation and HR.

urriculum

Introduction to Data Science

Learning Objectives - Get an introduction to Data Science in this module and see how Data Science

helps to analyze large and unstructured data with different tools.

Topics:

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

Statistical Inference

Learning Objectives - In this module, you will learn about different statistical techniques and

terminologies used in data analysis.

Topics:

What is Statistical Inference? Terminologies of Statistics

Measures of Centers Measures of Spread

Probability Normal Distribution

Binary Distribution

Data Extraction, Wrangling and Exploration

Learning Objectives - Discuss the different sources available to extract data, arrange the data in

structured form, analyze the data, and represent the data in a graphical format.

Topics:

Data Analysis Pipeline What is Data Extraction

Types of Data Raw and Processed Data

Data Wrangling Exploratory Data Analysis

Visualization of Data

Introduction to Machine Learning

Learning Objectives - Get an introduction to Machine Learning as part of this module. You will

discuss the various categories of Machine Learning and implement Supervised Learning Algorithms.

Topics:

What is Machine Learning? Machine Learning Use-Cases

Machine Learning Process Flow Machine Learning Categories

Supervised Learning algorithm: Linear

Regression and Logistic Regression