Data Science


Advanced Bootcamp Bigdata And Data Science By Spotle

This course by industry experts and academic leaders is designed for the people who want to build careers in this field

Advanced Bootcamp Bigdata And Data Science By Spotle


5 hours


Jan 2021

Last Update
Regular Price

What you will learn

Fundamentals Of Data Science

Fundamentals Of Statistics For Data Science

Predictive Modelling Techniques

Fundamentals Of Classification Analysis

Fundamentals Of Exploratory Analysis

Time Series Analysis With Case Studies

Fundamentals Of Big Data

Hadoop Fundamentals

HDFS Fundamentals

Apache Spark Fundamentals

Big Data On Cloud

Fundamentals Of Artificial Intelligence And Machine Learning

Supervised And Unsupervised Learning


Data science and big data have become key industry drivers in the global job and opportunity market. This course with mix of lectures from industry experts and Ivy League academics will help engineers, MBA students and young managers learn the fundamentals of big data and data science and their applications in business scenarios.

In this course you will be introduced to

1. Big data fundamentals

2. Hadoop Fundamentals

3. HDFS Fundamentals

4. Apache Spark Fundamentals

5. Big Data On Cloud

6. Data Science Fundamentals

7. AI, Machine Learning, Deep Learning Fundamentals

8. Fundamentals Of Statistics For Data Science

9. Fundamentals Of Predictive Modelling

10. Fundamentals Of Classification Analysis

11. Fundamentals Of Exploratory Analysis

12. Time Series Analysis With Case Studies


Introduction To Big Data

Big Data At A Glance

Overview of Big Data

Big Data Market Size

Big Data Perspective And Volume

Hadoop Fundamentals

Overview of Hadoop

Hadoop Architecture

Hadoop Components

HDFS Architecture, Benefits And Limitations

HDFS Architecture

HDFS Benefits

Issue With Small Files

Other Limitations

Apache Spark Fundamentals

Apache Spark Overview

Spark Architecture

Hadoop Vs Spark

Big Data On Cloud

Big Data On Cloud

Introduction To Data Science

Introduction To Data Science

Overview Of AI, Machine Learning And Deep Learning

Introduction To Artificial Intelligence

Introduction To Machine Learning

Introduction To Deep Learning

Fundamentals Of Machine Learning

Introduction To Supervised And Unsupervised Machine Learning

Introduction to Classification Problem and Decision Tree

Introduction to Cluster Analysis

Fundamentals Of Statistics For Data Science

Probability Refresher - Introduction, Rules and Conditional Probability

Bayes Theorem and Conditional Probability

Random Variables - Expectation and Variance

Random Variables and Distribution

Basic Statistics - I - Measuring Central Tendency

Basic Statistics II - Measuring Skewness and Kurtosis

Fundamentals Of Statistical Decision Making

Statistical Estimation

Test Of Hypothesis

The Basics Of Normality Test

Test Of Normality - Part 2

Test Of Normality - Part 3

Fundamentals Of Predictive Modelling

Understanding Linear Regression

Understanding Logistic Regression

Fundamentals Of Classification Analysis

Decision Tree Basics

Discriminant Analysis With Case Studies

Fundamentals Of Exploratory Analysis

Cluster Analysis - Features of Cluster Analysis

K-means Clustering

Hierarchical Clustering - Part 1

Hierarchical Clustering Case Studies

Hierarchical Clustering - Part 2


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