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

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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Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.

[Zaina-yhkc]

Thank you very much guys! All the best to everyone!

[gloriousezeamuzie]

This is an educative content but to be honest the tutors speak too fast that one can hardly follow up. No single break or pause in your speech. Please try to reduce your pace in your next videos and slow down a bit. That would really help. Thank you.

[Lathar]

It's just beyond my expectations 😊 Thank you so much team edureka🎉🎉I liked it soo much, , ❤❤i have seen this video many times

[sultanurrahmanshuvo]

Thanks edureka for this course which is helping me to build my basic. Can you please provide the pdf or notes you have regarding this course?

[EijazKhaja]

Thank you edureka for creating this video. I would appreciate it if you can share the notes :)

[nirajkamble]

This is very helpful thank you for your work . Could you please support PDF notes for this course. Thank you

[sindhugupta]

Very nice and helpful tutorial!! Thanks Edureka. Can I get pdf/notes for this session?

[soundaryah]

This video is really useful for me.... keep doing more videos.. please do share the pdf for this

[KrishnaPatil-bckj]

topics were really well explained except linear regression.

[Dhiepiga]

This is really useful kindly share the pdf documents pls

[nikhildesai]

Hi Edureka Team! This crash course has really helped in my basic and understanding. On my way to become a Data Scientist. Thank you! :D

Also is it possible to share PDF and practice notes?

[shwetachougule]

this video is veru usefull i want notes in pdf

[muhammadhassan]

Thank you edureka for this amazing tutorial...keep doing more videos.. please do share the pdf for this.

[nirmalkumar]

Thank you edureka for this amazing tutorial

[kandukuridhana]

It's amazing great content please send the pdf

[qudsiamehakgondal]

Can you share source codes and pdf of these lectures?

[Harish-yzdf]

Hello Edureka, Can I get PDF of this notes please!!