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π₯ Data Science Master Program (Use Code “πππππππππ”): https://www.edureka.co/masters-program/data-scientist-certification

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 for Beginners tutorial video:

00:00 Agenda

2:44 Introduction to Data Science

9:55 Data Analysis at Walmart

13:20 What is Data Science?

14:39 Who is a Data Scientist?

16:50 Data Science Skill Set

21:51 Data Science Job Roles

26:58 Data Life Cycle

30:25 Statistics & Probability

34:31 Categories of Data

34:50 Qualitative Data

36:09 Quantitative Data

39:11 What is Statistics?

41:32 Basic Terminologies in Statistics

42:50 Sampling Techniques

45:31 Random Sampling

46:20 Systematic Sampling

46:50 Stratified Sampling

47:54 Types of Statistics

50:38 Descriptive Statistics

55:52 Measures of Spread

55:56 Range

56:44 Inter Quartile Range

58:58 Variance

59:36 Standard Deviation

1:14:25 Confusion Matrix

1:19:16 Probability

1:24:14 What is Probability?

1:27:13 Types of Events

1:27:58 Probability Distribution

1:28:15 Probability Density Function

1:30:02 Normal Distribution

1:30:51 Standard Deviation & Curve

1:31:19 Central Limit Theorem

1:33:12 Types of Probablity

1:33:34 Marginal Probablity

1:34:06 Joint Probablity

1:34:58 Conditional Probablity

1:35:56 Use-Case

1:39:46 Bayes Theorem

1:45:44 Inferential Statistics

1:56:40 Hypothesis Testing

2:00:34 Basics of Machine Learning

2:01:41 Need for Machine Learning

2:07:03 What is Machine Learning?

2:09:21 Machine Learning Definitions

2:!1:48 Machine Learning Process

2:18:31 Supervised Learning Algorithm

2:19:54 What is Regression?

2:21:23 Linear vs Logistic Regression

2:33:51 Linear Regression

2:25:27 Where is Linear Regression used?

2:27:11 Understanding Linear Regression

2:37:00 What is R-Square?

2:46:35 Logistic Regression

2:51:22 Logistic Regression Curve

2:53:02 Logistic Regression Equation

2:56:21 Logistic Regression Use-Cases

2:58:23 Demo

3:00:57 Implement Logistic Regression

3:02:33 Import Libraries

3:05:28 Analyzing Data

3:11:52 Data Wrangling

3:23:54 Train & Test Data

3:20:44 Implement Logistic Regression

3:31:04 SUV Data Analysis

3:38:44 Decision Trees

3:39:50 What is Classification?

3:42:27 Types of Classification

3:42:27 Decision Tree

3:43:51 Random Forest

3:45:06 Naive Bayes

3:47:12 KNN

3:49:02 What is Decision Tree?

3:55:15 Decision Tree Terminologies

3:56:51 CART Algorithm

3:58:50 Entropy

4:00:15 What is Entropy?

4:23:52 Random Forest

4:27:29 Types of Classifier

4:31:17 Why Random Forest?

4:39:14 What is Random Forest?

4:51:26 How Random Forest Works?

4:51:36 Random Forest Algorithm

5:04:23 K Nearest Neighbour

5:05:33 What is KNN Algorithm?

5:08:50 KNN Algorithm Working

5:14:55 kNN Example

5:24:30 What is Naive Bayes?

5:25:13 Bayes Theorem

5:27:48 Bayes Theorem Proof

5:29:43 Naive Bayes Working

5:39:06 Types of Naive Bayes

5:53:37 Support Vector Machine

5:57:40 What is SVM?

5:59:46 How does SVM work?

6:03:00 Introduction to Non-Linear SVM

6:04:48 SVM Example

6:06:12 Unsupervised Learning Algorithms – KMeans

6:06:18 What is Unsupervised Learning?

6:06:45 Unsupervised Learning: Process Flow

6:07:17 What is Clustering?

6:09:15 Types of Clustering

6:10:15 K-Means Clustering

6:10:40 K-Means Algorithm Working

6:16:17 K-Means Algorithm

6:19:16 Fuzzy C-Means Clustering

6:21:22 Hierarchical Clustering

6:22:53 Association Clustering

6:24:57 Association Rule Mining

6:30:35 Apriori Algorithm

6:37:45 Apriori Demo

6:40:49 What is Reinforcement Learning?

6:42:48 Reinforcement Learning Process

6:51:10 Markov Decision Process

6:54:53 Understanding Q – Learning

7:13:12 Q-Learning Demo

7:25:34 The Bellman Equation

7:48:39 What is Deep Learning?

7:52:53 Why we need Artificial Neuron?

7:54:33 Perceptron Learning Algorithm

7:57:57 Activation Function

8:03:14 Single Layer Perceptron

8:04:04 What is Tensorflow?

8:07:25 Demo

8:21:03 What is a Computational Graph?

8:49:18 Limitations of Single Layer Perceptron

8:50:08 Multi-Layer Perceptron

8:51:24 What is Backpropagation?

8:52:26 Backpropagation Learning Algorithm

8:59:31 Multi-layer Perceptron Demo

9:01:23 Data Science Interview Questions

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## 29 Comments

## edureka!

May 12, 2022 22:26 pmGot a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka Data Science Masters Certification Curriculum, Visit our Website: http://bit.ly/3sw3tJj (Use Code "πππππππππ")

π΄Subscribe to Edureka YouTube channel for latest video updates: http://bit.ly/2ADbbb1

## payal sharma

May 12, 2022 22:26 pmThank you edureka for explaining each concept so nicely. Would it be possible for you to share the pdf or any document of the course in order to brush up the concepts quickly

## S K

May 12, 2022 22:26 pmWhere can i find ppt of this tutorial ?

## pinky v

May 12, 2022 22:26 pmMam please provide this ppt

## Khushi Lulla

May 12, 2022 22:26 pmHeyy, Can commerce student do this course? If Anyone has any idea please share β€οΈ

## Message For You

May 12, 2022 22:26 pmCan we get whole course pdf?

## Shuvam Bhowmick

May 12, 2022 22:26 pmDoes anyone know where I can find the Jupyter Notebook code files for this youtube video ? I really enjoyed seeing the code but if i had the file I could practice a bit more on my own.

## Mansi Gurnani

May 12, 2022 22:26 pmi am a commerecde student and want to learn data science skill for mt Mba will it be helpful or should I go in depth for more ?

## Jet Block

May 12, 2022 22:26 pm2:44 Introduction to Data Science

9:55 Data Analysis at Walmart

13:20 What is Data Science?

14:39 Who is a Data Scientist?

16:50 Data Science Skill Set

21:51 Data Science Job Roles

26:58 Data Life Cycle

30:25 Statistics & Probability

34:31 Categories of Data

34:50 Qualitative Data

36:09 Quantitative Data

39:11 What is Statistics?

41:32 Basic Terminologies in Statistics

42:50 Sampling Techniques

45:31 Random Sampling

46:20 Systematic Sampling

46:50 Stratified Sampling

47:54 Types of Statistics

50:38 Descriptive Statistics

55:52 Measures of Spread

55:56 Range

56:44 Inter Quartile Range

58:58 Variance

59:36 Standard Deviation

1:14:25 Confusion Matrix

1:19:16 Probability

1:24:14 What is Probability?

1:27:13 Types of Events

1:27:58 Probability Distribution

1:28:15 Probability Density Function

1:30:02 Normal Distribution

1:30:51 Standard Deviation & Curve

1:31:19 Central Limit Theorem

1:33:12 Types of Probablity

1:33:34 Marginal Probablity

1:34:06 Joint Probablity

1:34:58 Conditional Probablity

1:35:56 Use-Case

1:39:46 Bayes Theorem

1:45:44 Inferential Statistics

1:56:40 Hypothesis Testing

2:00:34 Basics of Machine Learning

2:01:41 Need for Machine Learning

2:07:03 What is Machine Learning?

2:09:21 Machine Learning Definitions

2:11:48 Machine Learning Process

2:18:31 Supervised Learning Algorithm

2:19:54 What is Regression?

2:21:23 Linear vs Logistic Regression

2:33:51 Linear Regression

2:25:27 Where is Linear Regression used?

2:27:11 Understanding Linear Regression

2:37:00 What is R-Square?

2:46:35 Logistic Regression

2:51:22 Logistic Regression Curve

2:53:02 Logistic Regression Equation

2:56:21 Logistic Regression Use-Cases

2:58:23 Demo

3:00:57 Implement Logistic Regression

3:02:33 Import Libraries

3:05:28 Analyzing Data

3:11:52 Data Wrangling

3:23:54 Train & Test Data

3:20:44 Implement Logistic Regression

3:31:04 SUV Data Analysis

3:38:44 Decision Trees

3:39:50 What is Classification?

3:42:27 Types of Classification

3:42:27 Decision Tree

3:43:51 Random Forest

3:45:06 Naive Bayes

3:47:12 KNN

3:49:02 What is Decision Tree?

3:55:15 Decision Tree Terminologies

3:56:51 CART Algorithm

3:58:50 Entropy

4:00:15 What is Entropy?

4:23:52 Random Forest

4:27:29 Types of Classifier

4:31:17 Why Random Forest?

4:39:14 What is Random Forest?

4:51:26 How Random Forest Works?

4:51:36 Random Forest Algorithm

5:04:23 K Nearest Neighbour

5:05:33 What is KNN Algorithm?

5:08:50 KNN Algorithm Working

5:14:55 kNN Example

5:24:30 What is Naive Bayes?

5:25:13 Bayes Theorem

5:27:48 Bayes Theorem Proof

5:29:43 Naive Bayes Working

5:39:06 Types of Naive Bayes

5:53:37 Support Vector Machine

5:57:40 What is SVM?

5:59:46 How does SVM work?

6:03:00 Introduction to Non-Linear SVM

6:04:48 SVM Example

6:06:12 Unsupervised Learning Algorithms – KMeans

6:06:18 What is Unsupervised Learning?

6:06:45 Unsupervised Learning: Process Flow

6:07:17 What is Clustering?

6:09:15 Types of Clustering

6:10:15 K-Means Clustering

6:10:40 K-Means Algorithm Working

6:16:17 K-Means Algorithm

6:19:16 Fuzzy C-Means Clustering

6:21:22 Hierarchical Clustering

6:22:53 Association Clustering

6:24:57 Association Rule Mining

6:30:35 Apriori Algorithm

6:37:45 Apriori Demo

6:40:49 What is Reinforcement Learning?

6:42:48 Reinforcement Learning Process

6:51:10 Markov Decision Process

6:54:53 Understanding Q – Learning

7:13:12 Q-Learning Demo

7:25:34 The Bellman Equation

7:48:39 What is Deep Learning?

7:52:53 Why we need Artificial Neuron?

7:54:33 Perceptron Learning Algorithm

7:57:57 Activation Function

8:03:14 Single Layer Perceptron

8:04:04 What is Tensorflow?

8:07:25 Demo

8:21:03 What is a Computational Graph?

8:49:18 Limitations of Single Layer Perceptron

8:50:08 Multi-Layer Perceptron

8:51:24 What is Backpropagation?

8:52:26 Backpropagation Learning Algorithm

8:59:31 Multi-layer Perceptron Demo

9:01:23 Data Science Interview Questions

## Dhaval Bendale

May 12, 2022 22:26 pmThanks for such a rich content on DataScience… Can you please share datasets with me used in video tutorial!!

## Azeem Wyne

May 12, 2022 22:26 pmGreat course. Well done!

## Prakriti Siradhne

May 12, 2022 22:26 pmThank you Edureka for this wonderful course. From where can we get the datasets used in this course? It would be great if you can share

## 1JS19CS025 Ananya

May 12, 2022 22:26 pmthank you for the beautiful course. is there document with the dataset used or answers to questions given here?

## Mahamat Mahamat Abdoulaye

May 12, 2022 22:26 pmAnd this kind of contents are for free π± Thank you from the bottom of the heart πβ€οΈ

## Shuhaib Muhammed

May 12, 2022 22:26 pmNice class

## Hussnain Arshad

May 12, 2022 22:26 pmyour teaching style is very simple and effective.Can you please share pdf of it for practice.Thanks

## Jeevraj Taralkar

May 12, 2022 22:26 pmCan you share PowerPoint, Dataset for practice. Thanks in advance

## OnePath Network

May 12, 2022 22:26 pmWhat if I use Minitab rather than R-Studio bcs I already used Minitab

## One World Gamers

May 12, 2022 22:26 pmi have diploma engineering in Electronics . can i go in this field ? how to start in data science

## Ashja Ahmed Khan

May 12, 2022 22:26 pm0.45 answer of bayes' theorem question

## Kamunyu Njoroge

May 12, 2022 22:26 pmWhen starting to learn Data Science, which programming language should I start with before embarking on Data Science?

## SHIVANI GUPTA

May 12, 2022 22:26 pmplz provide ppt of the lecture .

## Yadu Krishna

May 12, 2022 22:26 pmWhat a great contribution. Thank you Edureka for helping me understand the basics of Data science.

## K RAGASWARUPA

May 12, 2022 22:26 pmGreat job and nice explanation

It is difficult to make notes can you provide us the whole content in pdf or any other format ?

## Nikhila V

May 12, 2022 22:26 pmThanks for detailed explanation.Could you please share the slides used for this presentation

## victory news

May 12, 2022 22:26 pmsuper channel

## Sayantan Sinha

May 12, 2022 22:26 pmThank you Edureka for this wonderful course. From where can we get the datasets used in this course? It would be great if you could share them through a link.

## Kuldeep Singh

May 12, 2022 22:26 pmThank you Edureka for this wonderful course. Can you share the course contents – slides, python code notebooks and dataset

## Vidhisha Ashar

May 12, 2022 22:26 pmThank you Edureka for this wonderful course. Can you share the course contents – slides, python code notebooks and datasets ?