Python, Data Science and Machine Learning course
Artificial Intelligence
Development ,Data Science,Machine Learning
Lectures -64
Duration -16 hours
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Course Description
Are you ready to start your path to becoming a Data Scientist!
This course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!
Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!
This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost!
We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning:
- Programming with Python
- NumPy with Python
- Using pandas Data Frames to solve complex tasks
- Use pandas to handle Excel Files
- Web scraping with python
- Connect Python to SQL
- Use matplotlib and seaborn for data visualizations
- Machine Learning with SciKit Learn, including:
- Linear Regression
- K Nearest Neighbors
- Decision Trees
- Random Forests
- Natural Language Processing
- Support Vector Machines
- and much, much more!
- Enroll in the course and become a data scientist today!
Goals
- Use Python for Data Science and Machine Learning
- Learn to use Pandas for Data Analysis
- Learn to use Seaborn for statistical plots
- Use SciKit-Learn for Machine Learning Tasks
Prerequisites
- No Programming Experience needed. You will learn everything you need to know
Curriculum
Check out the detailed breakdown of what’s inside the course
Python Basics
19 Lectures
- Setup the Environment 10:45 10:45
- Print, comments 14:13 14:13
- Variables 17:28 17:28
- Strings 18:23 18:23
- Arithmetic 05:39 05:39
- Boolean Operations 14:47 14:47
- Boolean part 2 06:22 06:22
- Datatype Conversion 05:19 05:19
- Functions 17:25 17:25
- Functions 2 11:09 11:09
- Lambda 13:35 13:35
- Math Library 08:51 08:51
- OS Library 17:48 17:48
- If Statements 08:44 08:44
- While loop 13:17 13:17
- For Loop 16:38 16:38
- Object Oriented Programming (OOP) 15:50 15:50
- Constructor 12:49 12:49
- Example 29:33 29:33
Data Science Libraries
12 Lectures
Machine Learning
8 Lectures
Deep Neural Network (DNN)
6 Lectures
Convolutional Neural Network (CNN)
6 Lectures
Computer Vision Application
3 Lectures
Natural Language Processing
7 Lectures
Model Deployment
2 Lectures
Code of the Course
1 Lectures
Instructor Details
Hassan Fulaih
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