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Udemy – The Data Science Course 2019.4

Udemy - The Data Science Course 2019: Complete Data Science Bootcamp 2019-4

Free download Udemy – The Data Science Course 2019: Complete Data Science Bootcamp 2019-4 – The Data Science Course 2019: The Complete Data Science Bootcamp is a video tutorial for data science, mathematics, statistics, python, advanced statistics in Python and machines from the Udemy site. Data science is one of the best professions to grow this century, which is digital, programming and analytical. Therefore, it is not surprising that demand for data science in the labor market has increased. Most online courses focus on a particular subject, and understanding the training skills is very difficult. what’s the solution?

The science of data is a multidisciplinary field and includes a wide range of topics such as: Understanding the fields of science and data analysis, mathematics, statistics, Python, applying advanced statistical techniques in Python, visualizing data and Learning the car. By looking at this video tutorial, you will become a science specialist.

ویژگی دوره The Data Science Course 2019: Complete Data Science Bootcamp :

  • Perform linear and logistic regression in Python
  • Provide the tools needed to become a data scientist
  • Influencing interviewees through a thorough understanding of data science
  • Able to create machine learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • And…

Course profile:

  • Duration: 20.8 hours
  • English language
  • Number of lessons: 361 lessons
  • Movie format: AVC 1280 × 720
  • Sound: AAC 48KHz 2ch
  • مدرس : 365 Careers, 365 Careers Team

Course categories for The Data Science Course:

Course content
436 lectures 26:00:10

Part 1: Introduction
3 lectures 19:42

The Field of Data Science – The Various Data Science Disciplines
5 lectures 31:11

The Field of Data Science – Connecting the Data Science Disciplines
1 lecture 07:19

The Field of Data Science – The Benefits of Each Discipline
1 lecture 04:44

The Field of Data Science – Popular Data Science Techniques
11 lectures 53:34

The Field of Data Science – Popular Data Science Tools
1 lecture 05:51

The Field of Data Science – Careers in Data Science
1 lecture 03:29

The Field of Data Science – Debunking Common Misconceptions
1 lecture 04:10

Part 2: Probability
4 lectures 23:04

Combinatorics
11 lectures 42:56

Bayesian Inference
12 lectures 54:38

Probability Distributions
15 lectures 01:17:11

Probability in Other Fields
3 lectures 18:51

Part 3: Statistics
1 lecture 04:02

Statistics – Descriptive Statistics
22 lectures 48:11

Statistics – Practical Example: Descriptive Statistics
2 lectures 16:18

Statistics – Inferential Statistics Fundamentals
8 lectures 21:53

Statistics – Inferential Statistics: Confidence Intervals
15 lectures 44:25

Statistics – Practical Example: Inferential Statistics
2 lectures 10:08

Statistics – Hypothesis Testing
15 lectures 48:24

Statistics – Practical Example: Hypothesis Testing
2 lectures 07:19

Part 4: Introduction to Python
7 lectures 32:49

Python – Variables and Data Types
3 lectures 13:40

Python – Basic Python Syntax
7 lectures 11:20

Python – Other Python Operators
2 lectures 07:45

Python – Conditional Statements
4 lectures 13:29

Python – Python Functions
7 lectures 18:31

Python – Sequences
5 lectures 19:11

Python – Iterations
6 lectures 15:53

Python – Advanced Python Tools
4 lectures 12:56

Part 5: Advanced Statistical Methods in Python
1 lecture 01:27

Advanced Statistical Methods – Linear regression with StatsModels
11 lectures 40:55

Advanced Statistical Methods – Multiple Linear Regression with StatsModels
13 lectures 42:18

Advanced Statistical Methods – Linear Regression with sklearn
19 lectures 54:29

Advanced Statistical Methods – Practical Example: Linear Regression
9 lectures 38:01

Advanced Statistical Methods – Logistic Regression
16 lectures 40:49

Advanced Statistical Methods – Cluster Analysis
4 lectures 14:03

Advanced Statistical Methods – K-Means Clustering
15 lectures 49:01

Advanced Statistical Methods – Other Types of Clustering
3 lectures 13:34

Part 6: Mathematics
11 lectures 51:01

Part 7: Deep Learning
1 lecture 03:07

Deep Learning – Introduction to Neural Networks
12 lectures 42:38

Deep Learning – How to Build a Neural Network from Scratch with NumPy
5 lectures 20:36

Deep Learning – TensorFlow: Introduction
9 lectures 28:26

Deep Learning – Digging Deeper into NNs: Introducing Deep Neural Networks
9 lectures 25:44

Deep Learning – Overfitting
6 lectures 19:36

Deep Learning – Initialization
3 lectures 08:04

Deep Learning – Digging into Gradient Descent and Learning Rate Schedules
7 lectures 20:40

Deep Learning – Preprocessing
5 lectures 14:33

Deep Learning – Classifying on the MNIST Dataset
11 lectures 39:31

Deep Learning – Business Case Example
12 lectures 50:58

Deep Learning – Conclusion
7 lectures 17:42

Software Integration
5 lectures 29:38

Case Study – What’s Next in the Course?
3 lectures 10:14

Case Study – Preprocessing the ‘Absenteeism_data’
32 lectures 01:29:17

Case Study – Applying Machine Learning to Create the ‘absenteeism_module’
16 lectures 01:07:05

Case Study – Loading the ‘absenteeism_module’
4 lectures 11:00

Case Study – Analyzing the Predicted Outputs in Tableau
6 lectures 23:30

Prerequisite course

  • No prior experience is required. We will start from the very basics
  • You’ll need to install Anaconda. We will show you how to do that step by step
  • Microsoft Excel 2003, 2010, 2013, 2016, or 365

Installation guide

After Extract, please see the Player.

English subtitle

Quality: 720p

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Password (s): www.downloadly.ir

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13.5 GB

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