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

What you'll 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
Requirements
You will need to have a computer or a mobile handset with an internet connection
Knowledge of basic statistics will help
Description
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 to1. Big data fundamentals2. Hadoop Fundamentals3. HDFS Fundamentals4. Apache Spark Fundamentals5. Big Data On Cloud6. Data Science Fundamentals7. AI, Machine Learning, Deep Learning Fundamentals8. Fundamentals Of Statistics For Data Science9. Fundamentals Of Predictive Modelling10. Fundamentals Of Classification Analysis11. Fundamentals Of Exploratory Analysis12. Time Series Analysis With Case Studies

Overview

Section 1: Introduction To Big Data

Lecture 1 Big Data At A Glance

Lecture 2 Overview of Big Data

Lecture 3 Big Data Market Size

Lecture 4 Big Data Perspective And Volume

Section 2: Hadoop Fundamentals

Lecture 5 Overview of Hadoop

Lecture 6 Hadoop Architecture

Lecture 7 Hadoop Components

Section 3: HDFS Architecture, Benefits And Limitations

Lecture 8 HDFS Architecture

Lecture 9 HDFS Benefits

Lecture 10 Issue With Small Files

Lecture 11 Other Limitations

Section 4: Apache Spark Fundamentals

Lecture 12 Apache Spark Overview

Lecture 13 Spark Architecture

Lecture 14 Hadoop Vs Spark

Section 5: Big Data On Cloud

Lecture 15 Big Data On Cloud

Section 6: Introduction To Data Science

Lecture 16 Introduction To Data Science

Section 7: Overview Of AI, Machine Learning And Deep Learning

Lecture 17 Introduction To Artificial Intelligence

Lecture 18 Introduction To Machine Learning

Lecture 19 Introduction To Deep Learning

Section 8: Fundamentals Of Machine Learning

Lecture 20 Introduction To Supervised And Unsupervised Machine Learning

Lecture 21 Introduction to Classification Problem and Decision Tree

Lecture 22 Introduction to Cluster Analysis

Section 9: Fundamentals Of Statistics For Data Science

Lecture 23 Probability Refresher - Introduction, Rules and Conditional Probability

Lecture 24 Bayes Theorem and Conditional Probability

Lecture 25 Random Variables - Expectation and Variance

Lecture 26 Random Variables and Distribution

Lecture 27 Basic Statistics - I - Measuring Central Tendency

Lecture 28 Basic Statistics II - Measuring Skewness and Kurtosis

Section 10: Fundamentals Of Statistical Decision Making

Lecture 29 Statistical Estimation

Lecture 30 Test Of Hypothesis

Lecture 31 The Basics Of Normality Test

Lecture 32 Test Of Normality - Part 2

Lecture 33 Test Of Normality - Part 3

Section 11: Fundamentals Of Predictive Modelling

Lecture 34 Understanding Linear Regression

Lecture 35 Understanding Logistic Regression

Section 12: Fundamentals Of Classification Analysis

Lecture 36 Decision Tree Basics

Lecture 37 Discriminant Analysis With Case Studies

Section 13: Fundamentals Of Exploratory Analysis

Lecture 38 Cluster Analysis - Features of Cluster Analysis

Lecture 39 K-means Clustering

Lecture 40 Hierarchical Clustering - Part 1

Lecture 41 Hierarchical Clustering Case Studies

Lecture 42 Hierarchical Clustering - Part 2

Anyone with an interest in Data Science and Big Data and their applications in business