Introduction to Data Science Full Course

Agenda of Data Science Full Course

What is Data Science

Data Science Basics

Walmart use cases

Who is a Data Scientist

Role of a Data Scientist

Technologies to learn for a Data scientist

Data Scientist Roadmap

Data Science Salary

Statistics and Probability

Use Case

Confusion matrix

Probability

Bayes Theorem

Inferntial Statistics

What is Machine Learning

What is Regression in Machine Learning

Logistic Regression

Use case

Decision Tree Algorithm

What is Classification

Types of Classification

What is Decision Tree

Decesion Tree Terminologies

Random Forest

Working of Random Forest

RandomSampling with Replacement

Advantages of Random Forest

Hands-on Random forest

KNN Algorithm

Features of KNN

How Does KNN Algorithm Works

Hands-on KNN Algorithm

Naive Bayes Classifier

Support Vector Machine

K-means clustering Algorithm

Apriori Algorithm

Hands-on

Reinforcement Learning

Reinforcement Learning - Counter strike example

Q Learning

Defining a problem statement

The Bellman Equation

What is Deep Learning

Why do we need Artificial Neuron

What is Tensorflow

Tensorflow Code Basics

What is a Computational Graph

Limitation of a Single layer perception

Multi-layer Perceptron Use case

Data Scientist Resume

Data Science Interview Question & Answers

edureka!

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This Edureka Data Science Full Course video will help you understand and learn Data Science Algorithms in detail. This Data Science Tutorial is ideal for both beginners as well as professionals who want to master Data Science Algorithms. 

Below are the topics covered in this Data Science Full course tutorial: 
00:00:00 Introduction to Data Science Full Course
00:00:45 Agenda of Data Science Full Course
00:02:59 What is Data Science 
00:04:31 Data Science Basics 
00:07:13 Walmart use cases
00:12:05 Who is a Data Scientist
00:13:47 Role of a Data Scientist 
00:15:39 Technologies to learn for a Data scientist
00:44:16 Data Scientist Roadmap
01:00:55 Data Science Salary
01:09:44 Statistics and Probability
01:40:48 Use Case
01:50:43 Confusion matrix
02:00:15 Probability 
02:15:56 Bayes Theorem
02:22:22 Inferntial Statistics
02:31:37 Use Case
02:42:20 What is Machine Learning 
02:59:23 What is Regression in Machine Learning 
03:08:05 Use Case 
03:25:53 Logistic Regression 
03:32:46 Use case
04:14:25 Decision Tree Algorithm
04:15:01 What is Classification
04:19:12 Types of Classification
04:28:28 What is Decision Tree
04:35:35 Decesion Tree Terminologies
04:59:50 Random Forest 
05:03:11 Working of Random Forest 
05:04:08 RandomSampling with Replacement 
05:12:15 Advantages of Random Forest 
05:15:37 Hands-on Random forest 
05:27:01 KNN Algorithm
05:29:02 Features of KNN
05:37:17 How Does KNN Algorithm Works
05:42:50 Hands-on KNN Algorithm
05:59:30 Naive Bayes Classifier 
06:19:50 Support Vector Machine
06:45:16 K-means clustering Algorithm
07:05:27 Apriori Algorithm
07:21:14 Hands-on 
07:35:08 Reinforcement Learning 
07:38:25 Reinforcement Learning - Counter strike example
07:56:36 Q Learning 
07:57:34 Defining a problem statement
08:01:37 The Bellman Equation
08:19:25 What is Deep Learning 
08:23:24 Why do we need Artificial Neuron
08:33:55 What is Tensorflow
08:43:50 Tensorflow Code Basics
08:55:45 What is a Computational Graph
09:18:18 Limitation of a Single layer perception
09:25:54 Multi-layer Perceptron Use case
09:57:08 Data Scientist Resume
10:02:33 Data Science Interview Question & Answers 

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Data Science Full Course - 12 Hours | Data Science For Beginners | Data Science Tutorial | Edureka

Data Science Full Course - 12 Hours | Data Science For Beginners | Data Science Tutorial | Edureka

Data Science Full Course - 12 Hours | Data Science For Beginners | Data Science Tutorial | Edureka

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