Free Udemy Courses (24-25 January)
Complete WordPress Website Developer Course
Learn WordPress step by step to make beautiful blogs, websites,e-commerce sites to start your business ONLINE.
Detailed Description of the Course:
Free Udemy Courses (24-25 January), This is one of the best WordPress course you will ever find. WordPress is now powering more than 29% of all websites in the world, there’s never been a better time to build an income and a business around it.
This is the course of our students. New lecture are added every month and, at anytime on the request of the student.
You’re here because you want to master WordPress, right? Good idea. You’re in the right place. And, you can do it without learning any programming or coding.
While WordPress is open source, and because of that has thousands of developers building resources for it, it still takes quite a bit of learning to become a master at building and managing websites with it. But you don’t have to worry about anything. I will teach you everything that you need to know.
Deep Learning Foundation Training
Overview of Deep Learning concepts. Understand what are the Deep Learning Models, Platforms, Libraries and how they work
Detailed Description of the Course:
Deep Learning Foundation – Syllabus, Free Udemy Courses (24-25 January)
Module 1 – Introduction to Deep Learning
- Deep Learning: The Series Introduction
- What is a Neural Network
- Three reasons to go Deep
- Your choice of Deep Net
- Deep Learning Market
Module 2 – Deep Learning Models
- Restricted Boltzmann Machines
- Deep Belief Network
- Convolutional Network
- Recurrent Network
Module 3 – Additional Deep Learning Models
- Recursive Neural Tensor Network
- Generative Adversarial Networks
Module 4 – Deep Learning Platforms & Libraries
- What is a Deep Net Platform
- H2O ai
- Dato GraphLab
- What is a Deep Learning Library
Machine Learning Concepts and Application of ML using Python
Learn core concepts of Machine Learning. Apply ML techniques to real-world problems and develop AI/ML based applications
Detailed Description of the Course:
Free Udemy Courses (24-25 January), Uplatz offers this in-depth course on Machine Learning concepts and implementing machine learning with Python.
Objective: Learning basic concepts of various machine learning methods is primary objective of this course. This course specifically make student able to learn mathematical concepts, and algorithms used in machine learning techniques for solving real world problems and developing new applications based on machine learning.
Course Outcomes: After completion of this course, student will be able to:
1. Apply machine learning techniques on real world problem or to develop AI based application
2. Analyze and Implement Regression techniques
3. Solve and Implement solution of Classification problem
4. Understand and implement Unsupervised learning algorithms
- Python for Machine Learning
Introduction of Python for ML, Python modules for ML, Dataset, Apply Algorithms on datasets, Result Analysis from dataset, Future Scope of ML.
- Introduction to Machine Learning
What is Machine Learning, Basic Terminologies of Machine Learning, Applications of ML, different Machine learning techniques, Difference between Data Mining and Predictive Analysis, Tools and Techniques of Machine Learning.
- Types of Machine Learning
Supervised Learning, Unsupervised Learning, Reinforcement Learning. Machine Learning Lifecycle.
- Supervised Learning : Classification and Regression
Classification: K-Nearest Neighbor, Decision Trees, Regression: Model Representation, Linear Regression.
- Unsupervised and Reinforcement Learning
Clustering: K-Means Clustering, Hierarchical clustering, Density-Based Clustering.
Detailed Syllabus of Machine Learning Course
1. Linear Algebra
- Basics of Linear Algebra
- Applying Linear Algebra to solve problems
2. Python Programming
- Introduction to Python
- Python data types
- Python operators
- Advanced data types
- Writing simple Python program
- Python conditional statements
- Python looping statements
- Break and Continue keywords in Python
- Functions in Python
- Function arguments and Function required arguments
- Default arguments
- Variable arguments
- Build-in functions
- Scope of variables
- Python Math module
- Python Matplotlib module
- Building basic GUI application
- NumPy basics
- File system
- File system with statement
- File system with read and write
- Random module basics
- Pandas basics
- Matplotlib basics
- Building Age Calculator app
3. Machine Learning Basics
- Get introduced to Machine Learning basics
- Machine Learning basics in detail
4. Types of Machine Learning
- Get introduced to Machine Learning types
- Types of Machine Learning in detail
5. Multiple Regression
6. KNN Algorithm
- KNN intro
- KNN algorithm
- Introduction to Confusion Matrix
- Splitting dataset using TRAINTESTSPLIT
7. Decision Trees
- Introduction to Decision Tree
- Decision Tree algorithms
8. Unsupervised Learning
- Introduction to Unsupervised Learning
- Unsupervised Learning algorithms
- Applying Unsupervised Learning
9. AHC Algorithm
10. K-means Clustering
- Introduction to K-means clustering
- K-means clustering algorithms in detail
- Introduction to DBSCAN algorithm
- Understand DBSCAN algorithm in detail
- DBSCAN program
Build A Search Engine With Python: Computer Science & Python
AStateOfData.Com™ Computer Science With Python – Build A Search Engine With Python: Computer Science & Python
Detailed Description of the Course:
Free Udemy Courses (24-25 January), AStateOfData.Com™ Computer Science With Python: An Absolute Beginners Guide To Computer Science
- WHY THIS COURSE IS DIFFERENT?
Many of the online courses teach you to code but not the theory/way of thinking behind it why would we choose a while but not a for loop, why should we pass 2 parameters to a function but not only one?
This course will teach you how to think about solving coding problems throughout quizzes, there are 112 video format quizzes that aim to keep you engaged with the course and teach you the Python fundamentals in an easy to follow manner
- MEET THE INSTRUCTOR
We provide a platform for thousands of people to expand the understanding of programming and computer science. Founded in 2013 our mission is to spread the love for programming. To achieve this, we’re working hard on providing content that will help people build a solid foundation in those subjects.
- WHAT TO EXPECT
This course will help you to master the foundation and know-how to solve problems with Python code.
2. The content in a nutshell
- WHAT EACH UNIT IS ABOUT
This course will introduce you to the fundamental ideas in computing and teach you to read and write your own computer programs. We are going to do that in the context of building a web search engine.
Uint 1 will teach you the python grammar and show you how to use variables, strings, and some Python built-in functions to work on them in order to create a web crawler that makes use of those.
Unit 2 will take you in more depth in using procedures, loops, and the logical constructs in order to add more functionality to the crawler built-in unit 1.
Unit 3 is about managing data through mastering the use of the different data types to be able to create the search engine index.
Our biggest goal tho is to learn about computer science, So unit 4 focuses on teaching you how computers store data and how to be cost-effective when doing that. In addition to understanding the foundation of networks and data management.
By the end of unit 5, you’ll have a better understanding of how programs run and how to implement a hash table for our search engine.
Unit 6 will extend the grammar we introduced in unit 1 and will show you how to get the best result for a search query.
If the course gets much interaction and feedback, we’ll work on units to demonstrate how to code real-world Python applications
That’s the content in a nutshell. I hope you’re as excited as I’m to start this learning journey, so just the enrollment today and thank me later.
3. Who is the course for?
- BEGINNERS WHO WANT TO LEARN IN AN ACADEMIC WAY
This course is designed for extreme beginners with no computer science or programming background, it’ll help them get up and running with Python and give them a foundational understanding of computer science concepts.
- NOT FOR EXPERIENCED PROGRAMMERS
If you’re an experienced programmer or you already master Python and computer science concepts, then please do not take this course, unless you’d want a quick refresh on the Python programming foundation
4. Learning objectives
- MASTER THE FOUNDATION OF PROGRAMMING
This course focuses on helping extreme beginners in mastering computer science and python programming theory, in order to be able to solve coding problems or develop their own applications.
5. Conventions used in this course
Most of the snippets of code shown in this course (slides not interpreter), follows these color schemes:
- Variable names: green
- Operators: purple
- Python built-in functions: cyan
- Procedure names: blue
- Boolean Values: golden yellow
- Quizzes Questions and choices: orange
- Quizzes correct answer: green thick
- Quizzes false answer: red X
- Python symbols: pink
This course is the first of a multiple-courses sequence: Introduction to Computer Science and Programming Using Python. Together, they are designed to help people with no prior exposure to computer science or programming learn to think computationally and write programs to tackle useful problems.
Since these courses may be the only formal computer science courses many of the students take, we have chosen to focus on breadth rather than depth. The goal is to provide students with a brief introduction to many topics so they will have an idea of what is possible when they need to think about how to use computation to accomplish some goal later in their career. That said, they are not “computation appreciation” courses. They are challenging and rigorous courses in which the students spend a lot of time and effort learning to bend the computer to their will.
In this introduction to computer programming course, you’ll learn and practice key computer science concepts. You’ll learn Python, a powerful, easy-to-learn, and widely used programming language, and you’ll explore computer science basics, as you build your own programs.
This Computer science and programming using python course will introduce you to the fundamental ideas in computing and teach you to read and write your own computer programs.
Computer science is about how to solve problems, like building a search engine, by breaking them into smaller pieces and then precisely and mechanically describing a sequence of steps that you can use to solve each piece. And those steps can be executed by a computer.
In this course, we will not get into everything that you need to be a programmer, but we will cover the main ideas and learn a lot about computer science along the way.
By the end of this course, you will be fluently programming in Python and you’ll be so good at Python that you can get a job or use the language professionally.
You’ll cover all that you need to be an accomplished Python Programmer. Including:
- What is Programming
- Why programming
- Grammar and Python Rules
- Backus Naur Form
- Python Grammar
- Introducing Variables
- Variables Can Vary
- Introducing Strings
- Using Strings
- Strings and Numbers – String Concatenation
- String indexing
- String subsequences
- Understanding string selection
- Finding string in string
- Find Function With Parameter
- Extracting links from a web page
- Procedural abstraction
- Introducing procedures
- Procedure code
- Procedure input
- Procedure Output
- Return Statement
- Inc Procedure
- Sum procedure
- Square procedure
- Equality Comparison
- If statement
- The Or construct
- While loop
- Factorial Function
- Break Keyword
- Print all links from a seed page
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