Data Science Full Course - Learn Data Science in 10 Hours | Data Science For Beginners | Edureka

🔥 Data Science Course (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"): www.edureka.co...
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 course:
00:00 Data Science Full Course 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 Probability
1:33:34 Marginal Probability
1:34:06 Joint Probability
1:34:58 Conditional Probability
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
5:24:30 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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Got 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: bit.ly/3sw3tJj (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎") 🔴Subscribe to Edureka KZbin channel for latest video updates: bit.ly/2ADbbb1

[@ramasweety6162]

Hi is this 10hr video enough to get into data science jobs?

[@sourabhshrivastava4148]

edureka! Can you share all the presentation slides with us...

[@edurekaIN]

Hi Sourabh, You will find the presentations on our slideshare channel: www.slideshare.net/EdurekaIN

[@sofoworaololade3502]

Please how can I join edureka and get certification

[@edurekaIN]

Hi Ololade, kindly share your contact details, our team will reach you out with the details.

[@naresh7615]

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

[@nikhilsatija]

Thank You so much 👌🏻👍🏻 Edureka !! 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 2:11:48 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

[@sarthakjaiswal1341]

I love her teaching style...I'm gonna finish this in 2 days, it's so good and easy to learn...wasted 6 months in college learning this and they taught in much detail in 10 hours... it's amazing.

[@tzwacdastag8223]

Enjoy 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

[@thesoundguy712]

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

[@mailrama5192]

Im just 12 years old and excited about data science

[@priyankasawant2083]

Ohh wow great

[@narasimhanarasimha-kw5lf]

Even a beginner also learn easily to watch this video with free of cost, I really thankful to edureka. I started learning data science, now iam getting confidence on date science, because I have knowledge on DS is zero. From basics to insane level is available in this video. Tq for providing such a adequate information about a course

[@edurekaIN]

Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@malleswarimalli4557]

Nice explanation , very easy to understand to the beginners also #thank you for providing absolutely free in youtube..#very helpful for the researchers

[@zulfiqarali-zq1rg]

How this course help me during my reseach project I can't imagine.love all your team and expertise from neighbor pakistan😘😍

[@subharajhait4228]

I was looking for data science course for over a year and I don't have money to get admission and start course, this course will help me

[@najalam5033]

First of all, thank U so much Edureka for helping me out in my studies. It was such an amazing video. ❤ Secondly, want to know why U don't have any link to the power point of the lecture. Personally it's very difficult for me to write down everything and make notes. Could U plz share the PPP as well ? 🙏🙏🙏🌷🌷🌷

[@Amitkumar-lv4kp]

world level clear concept platform thanku so muchhh edureka

[@kiranmore3883]

2 hours.... continuously watching it and hopefully going to complete in 1-2 days only. Already in love with it. 😍 Very intuitive teaching. Thanks for providing this knowledge for free.

[@edurekaIN]

Thank you so much : ) We are glad to be a part of your learning journey. Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@girivardhanakumar4289]

Edureka team gets 5 star room in heaven Thanks for the amazing video I love this video a lot

[@MLICS2717]

Very very thankful to edureka for making it available on KZbin, absolutely free🙏😇👍

[@edurekaIN]

Thank you for watching our video. We are glad you loved the video. Do subscribe, like and share to stay connected with us. Cheers :)

[@JuanCoolDad]

This is an awesome tutorial! I could not believe you gave a 10hr tutorial for free! Wow! I am currently enrolled in a Data Science certification program & this tutorial will complement my school course. I plug in my headphones at work & listen away all day lol 😁👍Thank you!

[@edurekaIN]

Thanks for the compliment! We are glad that our video was of great help to you. Do subscribe to the channel and hit the bell icon to never miss an update from us in the future. Cheers!

[@donnelly5757]

This was awesome! Thank you! I will be that much more ready for when I begin my masters in data science next Fall. ❤️🧡💛 💚💙 💜 🖤

[@IsaacGeorge603]

Thank you Edureka for making this course free on KZbin

[@edurekaIN]

You are welcome Issac, Subscribe to our channel and stay tuned for more videos.

[@amitsingha1637]

30:30 -- Statistics and Probability

[@RenataAgathas]

Amo esses cursos! Vocês são awesome!!!!!! Muito obrigada! Greetings from Brazil =)

[@naveenkumar-bi8hh]

Great, eagerly waiting for this, I will be back ASAP with my exy

[@jasanisetu6679]

Thank you Edureka!! I just love it data science now.

[@CarGuy-lz2ge]

Looks brilliant. gonna start in a while..

[@mapmapo8247]

The course was great . I liked this . Could u please also make python full course but not beginner level but with a life examples. Would be so appreciative of that. 👍

[@edurekaIN]

Thanks for the compliment. We will forward your request to the content team. Do subscribe, like and share to stay connected with us. Cheers :)

[@dee2068]

It's a great beginners course. Loved it, thank you for getting me started off.

[@subhanshu3321]

Amazing video for beginner I'm from Pakistan

[@asthasrivastava4816]

Thanks for such a great course! However, can we confirm if categorical and discrete variables are the same thing? Isn't categorical the same as Qualitative like Good, Bad, Average, or Gender?

[@randomshite998]

Thank edureka a million times.. currently I'm pursuing data science but I'm unable to get a thing from my institute, they said they have 7+ years experienced tutor but he is experienced in job not in teaching..

[@edurekaIN]

We are very glad to hear that your a learning well with our contents 😊 continue to learn with us and don't forget to subscribe our channel so that you don't miss any updates !

[@yadukrishna7489]

What a great contribution. Thank you Edureka for helping me understand the basics of Data science.

[@edurekaIN]

Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@smitha1747]

You people are great thank you so much

[@mohitforimprovement]

Thanks a lot Edurika , I am in 9th for now and I am looking at data science as a career option . I have finished 10 minutes of the video and the topic really interested me , I will be finishing the video in 2 weeks and hopefully I get a fair idea of how Data science works . Again , thanks a lot 😄

[@DATAisFuturReHindi]

Excellent...thanks from DATA is FuturRe hindi channel Dedicated to Data Science

[@edurekaIN]

You're welcome 😊 Glad it was helpful!! Keep learning with us...

[@enoshsubba5875]

Great Job Edureka. Thank You. Appreciated. 🙌👏

[@ismailraini3431]

I am from non IT background.. today m starting..let c how much I will grasp this . 1) ultimate teaching skills, u wouldn't like to quit session....

[@edurekaIN]

We are super happy that Edureka is helping you learn better. Your support means a lot to us and it motivated us to create even better learning content and courses experience for you . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@thotachandrika5149]

It's really useful course ..thanks for providing it's for free

[@saanjalyvaishnav695]

i have an exam in 6 hours you saved my life thank you!!

[@yibeyibe389]

Amazing lecture!!Thank you!

[@sakuntalasahoo2886]

Heeee hii...I'm just starting data science courses but after seen this video..I'm full intrested to this course . Really it is very wonderful and also helpful video for me. Thanks a lot edureka .plz share me note or PDF

[@edurekaIN]

We are glad to have learners like you. Please do share your mail id so that we can send the notes or source codes. Do subscribe our channel and hit that bell icon to never miss an video from our channel

[@jennedanial8664]

Hello Edureka Team You guys are Doing Fabulous Job..... I am watching you courses past 10 days . Is your courses Cover all topics of Respected Course?????

[@dishantkumbhar8822]

Love u edureka! Really u just not made us understood concept but coding also. ❣️🙏

[@sujaulsuvon1472]

I think this course should be helpful for my academic education & carrier build up. ThAnK YoU😍 Note:I am a student at Department of Statistics BsC(Hons)

[@aryanmenon1691]

Edureka is great 👍👏😊 Much love to you guys..

[@deepthik4273]

Thank you so much.....

[@anashetty3968]

Can this courses useful for non technical background...I have have career break of 7 years due child care and full-time mum..and want to comback in work...

[@zawarallahbuxbhatti8727]

Hello edureka team, I really loved your efforts to make such helpful content, now I want to know is that all a data scientist needs to know or this was just for beginners? Thanks alot anyway 😊

[@edurekaIN]

Hi Zawar, thank you. The following Data Science Full Course tutorial is a structured module, covering all the topics that will be effectively emphasised in our certification course. If you wish to gain in-depth knowledge and become a certified Data Science professional, kindly visit: bit.ly/39jzdcY to view our certification courses and avail exclusive discounts using the code "KZbin20". Cheers :)

[@yes_i_am8378]

Awesome tutorial.. Got a alot of knowledge.

[@COSMO_INC1]

Appreciate your team on creating such detailed video about Data Science!

[@edurekaIN]

Thank you for your review : ) We are glad that you found our videos /contents useful . We are also trying our best to further fulfill your requirements and enhance your expirence :) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@CromaCampusOfficial]

Thanks for sharing this information Edureka. Really Helpful

[@Customercommunication]

Thank you, this is surely helpful.

[@omi_Prayagraj_wale]

It's very helpful video ...

[@ravisaxena1803]

Thank you so much for this great course. Could you provide us the whole content in pdf or any other format ?

[@rupeshsunuwar9145]

Thanks for the information and knowledge❤

[@ashjaahmedkhan3254]

0.45 answer of bayes' theorem question

[@riseandshine4514]

Probability question from baye's theorem, answer will be 0.5

[@afghanangaar]

Thank you EduReka.

[@chitraaaaa]

U ppl are doing amazing job...keep it up...

[@nathanadisu1855]

Excellent!

[@taslimuddinahmed4041]

1:44:00 Probability Question= Ans: 9/17

[@AH-cf9cv]

please give complete and full course ....👏👏👏👏

[@11Quote]

You are best bro

[@vaibhavmalviya9249]

Thankyou so much for this great course 🔥. Please if you can share the notes of this course in pdf format !

[@samindigodakanda4950]

Great work...thank you very much

[@earthquakeupdatebyupverma4165]

Excited to see n hear about the ML DS it's sciow and soread

[@mansigurnani4187]

i 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 ?

[@mbagraduateapplication5616]

Nice course! Greetings from UK

[@DJ-Rudra]

Just Completed the 10hrs theory.

[@unsharma9229]

I would like to take up the course for Data science with python.

[@edurekaIN]

Here's a link to our course: bit.ly/2IhxgQa

[@stayawesomewithhridya2370]

Can't stop me to comment here.. Thanks you edureka... Superb course.

[@edurekaIN]

Thank you so much :) Thanks for your supporting

[@FrustratedEngineer_]

This is amazing ... Where was this all my engineering life ...

[@panchanansahoo1463]

Thanks edureka for this video 💗💗

[@niranjannanjayyanamath9306]

Got good experiences..

[@risat01]

Good video thx to edureka team, i hope i can read modul .pdf

[@pradheeshrj3761]

Thanku 🤩 So Much Ｅｄｕｒｅｋａ!

[@user-vw9ep9pt4u]

thank you so much edureka

[@vishakshetty3214]

Easy to understand😉

[@suddha1000]

Thanks for making it simple and clear.

[@shradhabhadoria1454]

saw till 1hr . it's great . thanks a lot to the creators .

[@dishantkumbhar8822]

Guys this is really an awesome tutorial, you won't find out on another channel. Like if u r watching this video Thank you Edureka for making us understand complex thing in simplest manner.

[@dailywebmoments]

thanks edureka for providing free education 😍😍😍😍 from Pak

[@edurekaIN]

You are most welcome, Tasadduq. Don't forget to subscribe our channel.

[@reniba2383]

Yes I got it

[@manubhargav1054]

Thankyou for the course. Would you please share the datasheet so it would be easier to refer?

[@edurekaIN]

Hi please share your mail id to share the data sheet :) We'll Update you soon ! Do Subscribe the channel to keep updated

[@dhavalbendale5509]

Thanks for such a rich content on DataScience... Can you please share datasets with me used in video tutorial!!

[@edurekaIN]

Hi ! Good to know that our videos are helping you to learn better :) Please share your mail id to share the data sheets :)We’ll update you soon . Do subscribe the channel for more updates : )

[@saurav_advait]

Thank you for keeping it free for all.. gratitude :)

[@kanupriyamittal1998]

I love the way you guys teach. Could I please get the presentation and the materials via which you have taught? They are absolutely the best!

[@edurekaIN]

Hi Kanupriya, you will find the presentations on our slideshare channel: www.slideshare.net/EdurekaIN

[@nishaafrin551]

Thank You sooooo much..... from malaysia ❤❤❤

[@akinkunmiojo7849]

How do I install all these packages on my MacBook, I mean R, python, tableau, SQL and Matlab

[@harshranjan6535]

Thank you, it helps me lot

[@dinishikkha4836]

very nice video. I followed by edureka videos .. I had so much learned in this site like python,java and AI

[@edurekaIN]

Thanks Nahar, don't forget to subscribe our channel.

[@suryanshsingh1472]

it might be possible.

[@techworld_jroshan]

This is amazing or awesome youtube channel for computer science and technology or coding language or programming language 🙏🙏 I also want to started teeching about this topic. Nobody don't miss any video from this channel

[@edurekaIN]

Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@kshitij618]

great teaching motive is clear

[@edurekaIN]

Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@nagaraju.a8424]

can u share the slides presentation link for these video..........

[@hritvedahir7797]

Is discrete data categorical? Really because according to my knowledge Qualitative data is called as categorical. Please explain

[@pavankalidindi5950]

Thank you Edureka for this informative course. Can you share the course contents - slides, python code notebooks, and datasets?

[@edurekaIN]

Hi great to hear from you :) please share your mail id ! so that we can share the data sheet with you :)Do subscribe the channel for more updates : )

[@abhisheksingh2197]

Thanks for that....

[@nishantsharma3413]

Very insightful and thank you for keeping it free. I really liked the content it's very well structured. It's worth your 10 hours guys! kudos to you Ma'am keep the good work👍

[@edurekaIN]

Glad you enjoyed it! Happy Learning!😊

[@rubeenabegum8095]

Thank 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.

[@edurekaIN]

Yes sure, kindly drop your mail id

[@utkarshanishad2413]

Thank you so much edureka! for this video. This is so beneficial for me as a beginner. 😊😊

[@edurekaIN]

You are most welcome. We are glad we could help. Do subscribe to our channel to stay posted on upcoming tutorials.

[@khayimaarnisti1621]

Thank you very much for your video tutorials, its very help full to me