Udemy Free Courses
Python Complete Course For Beginners
This course is a depth introduction to both fundamental python programming concepts and the Python programming language.
Detailed Description of the Course:
Learn Python From Beginner To Advanced Level By Demonstrations
- The course is created thorough, extensive, but easy to follow content which you’ll easily understand and absorb.
The course starts with the basics, including Python fundamentals, programming, and user interaction.
The curriculum is going to be very hands-on as we walk you from start to finish to become a professional Python developer. We will start from the very beginning by teaching you Python basics and programming fundamentals, and then going into advanced topics and different career fields in Python so you can get real-life practice and be ready for the real world.
- While it is easy for beginners to learn, it is widely used in many scientific areas for data exploration. This course is an introduction to the Python programming language for students without prior programming experience. We cover data types, control flow, object-oriented programming, and graphical user interface-driven applications
- Master the fundamentals of writing Python scripts
- Learn core Python scripting elements such as variables and flow control structures
- Discover how to work with lists and sequence data
- Write Python functions to facilitate code reuse
- Use Python to read and write files
- Make their code robust by handling errors and exceptions properly
- Explore Python’s object-oriented features
- Search text using regular expressions
- The topics covered in this course are:
* Beginner to Expert Python contents:
Keywords and Identifiers
Object-Oriented Programming with Python
Functional Programming with Python
Testing in Python
- See you inside the course!
Adobe illustrator CC 2021 essential class ||GET CERTIFICATE
Complete adobe illustrator CC 2021 essential training course from scratch for beginners.
Detailed Description of the Course:
Hello guys, My name is Anwer Khan and I will be your instructor throughout this course. I am been using Adobe illustrator CC for many years and I have created lots of logos and design many mobile applications for my clients.
Now this will be the essential course for anyone who wants to learn Adobe illustrator CC. I will teach you Adobe illustrator CC from scratch and you will master each and every tool available in illustrator.
I will not just teach you about tools in illustrator but also how to create different shapes using these tools. So once you complete this course you will be able to create any stuff you imagine. Whether it is a logo illustration or any shape and you will be able to create that stuff easily.
Now, this is a complete beginner course in which you will learn Adobe illustrator CC from scratch. You don’t need to have any previous experience in Adobe illustrator. We will learn each and every tool and I will also show you how to use these tools and draw your stuff.
Now let’s talk about the course structure, first of all, this course will be straight to the point, So we will not talk about unwanted stuff, therefore, we will cover more in less time then after introduction in the first section, we will talk about selection tools and pen tool. We will master the selection tool, pen tool and direct selection tool. We will learn these tools and do cool stuff using these tools.
After that in the second section, we will take a look at strokes and rotate tool and I will also show you how to use these tools and create really cool stuff.
Next, we will master colors, gradients and the pathfinder tool. Then in the fourth section, you will learn how to use the text tool, brushes and masks. We will also do fun practice along the way.
Next, we will also learn the 3D tool, mesh, perspective grid and blend tool. We will also learn all the other tools and panels along the way, So don’t worry about it.
Finally, in the last section, we will learn transform options, tracing images and I will also show you how to create reusable actions.
So, if you want to master Adobe illustrator CC then I hope i will see you in the course.
The Complete Web Development Course with PHP, PDO & MySQL
Learn Everything to be a Professional PHP Developer by Building Fully Functional Website with Admin Panel
Md. A. Barik
Detailed Description of the Course:
Welcome to the “The Complete Web Development Course with PHP, PDO & MySQL” course!
Are you new to PHP or Need a bit of refresher?
Then this course will help you get all the fundamentals web development from start to finish with PHP, PDO & MYSQL and we’ll all end up by building a complete blogging website with pretty cool admin panel at the same place.
I promise you that I will not waste your time ~ I will straightly jump right into the topic that we need to build a complete website with all necessary functionality without wasting your valuable time! My another promise is that ~ If you can finished this course properly then you don’t need any other courses to learn web development with PHP, PDO & MySQL. You will gain all the information that you need to be a professional PHP developer. After taking this course ~ you will be able to build any type of website that you need to build with PHP programming language.
Your money investment in this course will be multiplied time to time:
With over 120 lectures and with 10 hours+ of video content, you can bet your money will be well spent in this course.
FAQ (Frequently Ask Question):
Q: Is PHP worth it to learn?
A: Big Word ***YES***
PHP is one of the best programming languages to build website in the world. Some of the top tech company still using PHP like Facebook, Wekipedia, Udemy and much more.
Q: Can I make Money if I know PHP?
A: Yes you can!
Go over some freelancing website then you will see there are a lot of freelancing job available for you if you know PHP. You will see so many projects waiting for people.
Q: Is it possible to land a job if I know PHP?
A: Yes its possible!
Visit Indeed or LinkedIn website there you will see a lot of job posting for PHP developer. So take your time.
This Course Covers the following:
- How to use database with PHP
- How to build website using MySQL Database
- How to use MySQL database with PDO
- Form in PHP
- Password hashing
- Login system
- Sign up system
- Forgot password functionality
- Remember me functionality
- Simple messaging system
- Comments and messages notifications
- Pretty cool looking admin panel
- How to build search engine
- Implementation of pagination
- And much more…
With the awesome project we will be building, you will learn all the skills need to land a job or build a project. I walk through step by step on everything from scratch.
We have 30 days money back guarantee, no question ask!
Artificial Neural Networks for Business Managers in R Studio
You do not need coding or advanced mathematics background for this course. Understand how predictive ANN models work
Detailed Description of the Course:
You’re looking for a complete Artificial Neural Network (ANN) course that teaches you everything you need to create a Neural Network model in R, right?
You’ve found the right Neural Networks course!
After completing this course you will be able to:
- Identify the business problem which can be solved using Neural network Models.
- Have a clear understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc.
- Create Neural network models in R using Keras and Tensorflow libraries and analyze their results.
- Confidently practice, discuss and understand Deep Learning concepts
How this course will help you?
A Verifiable Certificate of Completion is presented to all students who undertake this Neural networks course.
If you are a business Analyst or an executive, or a student who wants to learn and apply Deep learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the most advanced concepts of Neural networks and their implementation in R Studio without getting too Mathematical.
Why should you choose this course?
This course covers all the steps that one should take to create a predictive model using Neural Networks.
Most courses only focus on teaching how to run the analysis but we believe that having a strong theoretical understanding of the concepts enables us to create a good model . And after running the analysis, one should be able to judge how good the model is and interpret the results to actually be able to help the business.
What makes us qualified to teach you?
The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Deep learning techniques and we have used our experience to include the practical aspects of data analysis in this course
We are also the creators of some of the most popular online courses – with over 250,000 enrollments and thousands of 5-star reviews like these ones:
This is very good, i love the fact the all explanation given can be understood by a layman – Joshua
Thank you Author for this wonderful course. You are the best and this course is worth any price. – Daisy
Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.
Download Practice files, take Practice test, and complete Assignments
With each lecture, there are class notes attached for you to follow along. You can also take practice test to check your understanding of concepts. There is a final practical assignment for you to practically implement your learning.
What is covered in this course?
This course teaches you all the steps of creating a Neural network based model i.e. a Deep Learning model, to solve business problems.
Below are the course contents of this course on ANN:
- Part 1 – Setting up R studio and R Crash course
This part gets you started with R.
This section will help you set up the R and R studio on your system and it’ll teach you how to perform some basic operations in R.
- Part 2 – Theoretical Concepts
This part will give you a solid understanding of concepts involved in Neural Networks.
In this section you will learn about the single cells or Perceptrons and how Perceptrons are stacked to create a network architecture. Once architecture is set, we understand the Gradient descent algorithm to find the minima of a function and learn how this is used to optimize our network model.
- Part 3 – Creating Regression and Classification ANN model in R
In this part you will learn how to create ANN models in R Studio.
We will start this section by creating an ANN model using Sequential API to solve a classification problem. We learn how to define network architecture, configure the model and train the model. Then we evaluate the performance of our trained model and use it to predict on new data. We also solve a regression problem in which we try to predict house prices in a location. We will also cover how to create complex ANN architectures using functional API. Lastly we learn how to save and restore models.
We also understand the importance of libraries such as Keras and TensorFlow in this part.
- Part 4 – Data Preprocessing
In this part you will learn what actions you need to take to prepare Data for the analysis, these steps are very important for creating a meaningful.
In this section, we will start with the basic theory of decision tree then we cover data pre-processing topics like missing value imputation, variable transformation and Test-Train split.
- Part 5 – Classic ML technique – Linear Regression
This section starts with simple linear regression and then covers multiple linear regression.
We have covered the basic theory behind each concept without getting too mathematical about it so that you
understand where the concept is coming from and how it is important. But even if you don’t understand
it, it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures.
We also look at how to quantify models accuracy, what is the meaning of F statistic, how categorical variables in the independent variables dataset are interpreted in the results and how do we finally interpret the result to find out the answer to a business problem.
By the end of this course, your confidence in creating a Neural Network model in R will soar. You’ll have a thorough understanding of how to use ANN to create predictive models and solve business problems.
Go ahead and click the enroll button, and I’ll see you in lesson 1!
Below are some popular FAQs of students who want to start their Deep learning journey-
Why use R for Deep Learning?
Understanding R is one of the valuable skills needed for a career in Machine Learning. Below are some reasons why you should learn Deep learning in R
1. It’s a popular language for Machine Learning at top tech firms. Almost all of them hire data scientists who use R. Facebook, for example, uses R to do behavioral analysis with user post data. Google uses R to assess ad effectiveness and make economic forecasts. And by the way, it’s not just tech firms: R is in use at analysis and consulting firms, banks and other financial institutions, academic institutions and research labs, and pretty much everywhere else data needs analyzing and visualizing.
2. Learning the data science basics is arguably easier in R. R has a big advantage: it was designed specifically with data manipulation and analysis in mind.
3. Amazing packages that make your life easier. Because R was designed with statistical analysis in mind, it has a fantastic ecosystem of packages and other resources that are great for data science.
4. Robust, growing community of data scientists and statisticians. As the field of data science has exploded, R has exploded with it, becoming one of the fastest-growing languages in the world (as measured by StackOverflow). That means it’s easy to find answers to questions and community guidance as you work your way through projects in R.
5. Put another tool in your toolkit. No one language is going to be the right tool for every job. Adding R to your repertoire will make some projects easier – and of course, it’ll also make you a more flexible and marketable employee when you’re looking for jobs in data science.
What is the difference between Data Mining, Machine Learning, and Deep Learning?
Put simply, machine learning and data mining use the same algorithms and techniques as data mining, except the kinds of predictions vary. While data mining discovers previously unknown patterns and knowledge, machine learning reproduces known patterns and knowledge—and further automatically applies that information to data, decision-making, and actions.
Deep learning, on the other hand, uses advanced computing power and special types of neural networks and applies them to large amounts of data to learn, understand, and identify complicated patterns. Automatic language translation and medical diagnoses are examples of deep learning.
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