Top 10 Python Online Courses On Udemy: Become a Python Programmer

Do you want to Become a Professional Python Programmer? Then these Top 20 Python Online Courses On Udemy might be the right tools to get you on the path as a beginner.
Top 10 Python Online Courses On Udemy: Become a Python Programmer

Udemy.com is the world's biggest online learning platform. It is aimed at professional adults and students. Udemy have more than 40 million students who have access to over 30 million minutes of content on Udemy. More than 50,000 instructors are teaching 130,000 courses in over 60 languages.

Students rate courses after taking them. Here are the highest rated python courses on Udemy:

1- Complete Python Bootcamp: Go from zero to hero in Python 3

Learn Python like a Professional! Start from the basics and go all the way to creating your own applications and games!

Become a Python Programmer and learn one of employer's most requested skills of 2018!

This is the most comprehensive, yet straight-forward, course for the Python programming language on Udemy! Whether you have never programmed before, already know basic syntax, or want to learn about the advanced features of Python, this course is for you! In this course we will teach you Python 3. (Note, we also provide older Python 2 notes in case you need them)

With over 100 lectures and more than 20 hours of video this comprehensive course leaves no stone unturned! This course includes quizzes, tests, and homework assignments as well as 3 major projects to create a Python project portfolio!

This course will teach you Python in a practical manner, with every lecture comes a full coding screencast and a corresponding code notebook! Learn in whatever manner is best for you!

This course will start by helping you get Python installed on your computer, regardless of your operating system, whether its Linux, MacOS, or Windows.

What you'll learn

Learn to use Python professionally, learning both Python 2 and Python 3!
Create games with Python, like Tic Tac Toe and Blackjack!
Learn advanced Python features, like the collections module and how to work with timestamps!
Learn to use Object Oriented Programming with classes!
Understand complex topics, like decorators.
Understand how to use both the Jupyter Notebook and create .py files
Get an understanding of how to create GUIs in the Jupyter Notebook system!
Build a complete understanding of Python from the ground up!

Take this Course for $12.99

2- REST APIs with Flask and Python

Build professional REST APIs with Python, Flask, Flask-RESTful, and Flask-SQLAlchemy

Are you tired of boring, outdated, incomplete, or incorrect tutorials? I say no more to copy-pasting code that you don’t understand.

Who this course is for:

Students wanting to extend the capabilities of mobile and web applications by using server-side technologies
Software developers looking to expand their skill-set by learning to develop professional grade REST APIs
Those looking to learn Python while specifically catering to web services

You'll be able to...

Create resource-based, production-ready REST APIs using Flask and popular extensions;

Using SQLAlchemy to easily and efficiently store resources to a database; and

Understand the complex intricacies of deployments and performance of REST APIs.

What you'll learn

Connect web or mobile applications to databases and servers via REST APIs
Create secure and reliable REST APIs which include authentication, logging, caching, and more
Understand the different layers of a web server and how web applications interact with each other
Handle seamless user authentication with advanced features like token refresh
Handle log-outs and prevent abuse in your REST APIs with JWT blacklisting
Develop professional-grade REST APIs with expert instruction


3- Machine Learning A-Z™: Hands-On Python & R In Data Science

Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.

This course is fun and exciting, but at the same time dive deep into Machine Learning. It is structured the following way:

Part 1 - Data Preprocessing
Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
Part 4 - Clustering: K-Means, Hierarchical Clustering
Part 5 - Association Rule Learning: Apriori, Eclat
Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP
Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA
Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.

And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.

Who this course is for:

Anyone interested in Machine Learning.
Students who have at least high school knowledge in math and who want to start learning Machine Learning.
Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
Any students in college who want to start a career in Data Science.
Any data analysts who want to level up in Machine Learning.
Any people who are not satisfied with their job and who want to become a Data Scientist.
Any people who want to create added value to their business by using powerful Machine Learning tools.

What you'll learn

Master Machine Learning on Python & R
Have a great intuition of many Machine Learning models
Make accurate predictions
Make powerful analysis
Make robust Machine Learning models
Create strong added value to your business
Use Machine Learning for personal purpose
Handle specific topics like Reinforcement Learning, NLP and Deep Learning
Handle advanced techniques like Dimensionality Reduction
Know which Machine Learning model to choose for each type of problem
Build an army of powerful Machine Learning models and know how to combine them to solve any problem


4- Python for Data Science and Machine Learning Bootcamp

Are you ready to start your path to becoming a Data Scientist! 

This comprehensive 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 course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

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! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy!

This course will 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
Use plotly for interactive visualizations
Machine Learning with SciKit Learn, including:
Linear Regression
K Nearest Neighbors
K Means Clustering
Decision Trees
Random Forests
Natural Language Processing
Neural Nets and Deep Learning
Support Vector Machines
and much, much more!


5- The Python Mega Course: Build 10 Real World Applications

Start Python from the basics and learn how to create 10 amazing and professional Python programs used in the real world!

The Python Mega Course is one of the top online courses to learn Python programming and it has over 130,000 enrolled students. The course is for people with little or no previous programming experience. The Python Mega Course follows a modern-teaching approach where students learn by doing. You will start Python from scratch by creating simple programs first. 

Once you learn the basics you will then be guided on how to create 10 real-world complex applications in Python 3 through easy video explanations and support by the course instructor. Some of the applications you will build during the course with Python are database apps, web apps, desktop apps, web scraping scripts, webcam object detectors, web maps, data visualization dashboards, and more. These programs are not only great examples to master Python, you can also use any of the programs as your own portfolio once you have built the program.

By buying the course you will gain lifetime access to all its videos, coding exercises, quizzes, code notebooks, cheatsheets, and the Q&A inside the course where you can ask your questions and get an answer the same day. On top of that you are covered by the Udemy 30-day money back guarantee, so you can easily return the course if you don't like it.

If you don't know anything about Python, do not worry! In the first 12 sections, you will learn Python basics such as functions, loops, and conditionals and learn how to apply the basics by doing some examples. If you already know the basics, then the first 12 sections can serve as a refresher. The other 20 sections focus entirely on building real-world applications. The applications you will build cover a wide range of interesting topics:

Web applications 

Desktop applications 

Database applications 

Web scraping 

Web mapping 

Data analysis

Data visualization

Computer vision

Object-Oriented Programming

Specifically, the 10 Python applications you will build are:

A program that returns English-word definitions

A program that blocks access to distracting websites 

A web map visualizing volcanoes and population data

A portfolio website

A desktop-graphical program with a database backend

A webcam motion detector

A web scraper of real estate data

An interactive web graph

A database web application

A web service that converts addresses to geographic coordinates

To consider yourself a professional programmer you need to know how to make professional programs and there's no other course that teaches you that, so join thousands of other students who have successfully applied their Python skills in the real world. Sign up and start learning Python today!

Who this course is for:

Those with no prior knowledge of Python.
Those who know Python basics and want to master Python


6- Learning Python for Data Analysis and Visualization

This course will give you the resources to learn python and effectively use it analyze and visualize data! Start your career in Data Science!

You'll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data. 

You will also get lifetime access to over 100 example python code notebooks, new and updated videos, as well as future additions of various data analysis projects that you can use for a portfolio to show future employers! 

    By the end of this course you will: 

  - Have an understanding of how to program in Python. 

  - Know how to create and manipulate arrays using numpy and Python. 

  - Know how to use pandas to create and analyze data sets. 

  - Know how to use matplotlib and seaborn libraries to create beautiful data visualization. 

  - Have an amazing portfolio of example python data analysis projects! 

- Have an understanding of Machine Learning and SciKit Learn!

With 100+ lectures and over 20 hours of information and more than 100 example python code notebooks, you will be excellently prepared for a future in data science! 

Who this course is for:

Anyone interested in learning more about python, data science, or data visualizations.
Anyone interested about the rapidly expanding world of data science!


7- Python and Django Full Stack Web Developer Bootcamp

Learn to build websites with HTML , CSS , Bootstrap , Javascript , jQuery , Python 3 , and Django!

Welcome to the Python and Django Full Stack Web Developer Bootcamp! In this course we cover everything you need to know to build a website using Python, Django, and many more web technologies!

Whether you want to change career paths, expand your current skill set, start your own entrepreneurial business, become a consultant, or just want to learn, this is the course for you!

This course is designed so that anyone can learn how to become a web developer. We teach you how to program by using HD Video Lectures, Walkthrough Code Projects, Exercises, Concept Presentation Slides, Downloadable Code Notes, Reading Assignments, and much more! 

What you'll learn

Create a fully functional web site using the Full-Stack with Django 1.11
Learn how to use HTML to create website content
Use CSS to create beautifully styled sites
Learn how to take advantage of Bootstrap to quickly style sites
Use Javascript to interact with sites on the Front-End
Learn how to use jQuery to quickly work with the DOM
Understand HTTP requests
Create fantastic landing pages
Learn the power of Python to code out your web applications
Use Django as a back end for the websites
Implement a full Models-Views-Templates structure for your site


8- Python for Financial Analysis and Algorithmic Trading

Learn numpy , pandas , matplotlib , quantopian , finance , and more for algorithmic trading with Python!

Welcome to Python for Financial Analysis and Algorithmic Trading! Are you interested in how people use Python to conduct rigorous financial analysis and pursue algorithmic trading, then this is the right course for you!

This course will guide you through everything you need to know to use Python for Finance and Algorithmic Trading! You'll start off by learning the fundamentals of Python, and then proceed to learn about the various core libraries used in the Py-Finance Ecosystem, including jupyter, numpy, pandas, matplotlib, statsmodels, zipline, Quantopian, and much more!

 The course covers the following topics used by financial professionals:

Python Fundamentals
NumPy for High Speed Numerical Processing
Pandas for Efficient Data Analysis
Matplotlib for Data Visualization
Using pandas-datareader and Quandl for data ingestion
Pandas Time Series Analysis Techniques
Stock Returns Analysis
Cumulative Daily Returns
Volatility and Securities Risk
EWMA (Exponentially Weighted Moving Average)
Statsmodels
ETS (Error-Trend-Seasonality)
ARIMA (Auto-regressive Integrated Moving Averages)
Auto Correlation Plots and Partial Auto Correlation Plots
Sharpe Ratio
Portfolio Allocation Optimization 
Efficient Frontier and Markowitz Optimization
Types of Funds
Order Books
Short Selling
Capital Asset Pricing Model
Stock Splits and Dividends
Efficient Market Hypothesis
Algorithmic Trading with Quantopian
Futures Trading

Who this course is for:

Someone familiar with Python who wants to learn about Financial Analysis!


9- Python for Finance: Investment Fundamentals & Data Analytics

Learn Python Programming and Conduct Real-World Financial Analysis in Python - Complete Python Training

Do you want to learn how to use Python in a working environment?

Are you a young professional interested in a career in Data Science?  

Would you like to explore how Python can be applied in the world of Finance and solve portfolio optimization problems?  

If so, then this is the right course for you!  

We are proud to present Python for Finance: Investment Fundamentals and Data Analytics – one of the most interesting and complete courses we have created so far. It took our team slightly over four months to create this course, but now, it is ready and waiting for you.  

An exciting journey from A-Z.  

If you are a complete beginner and you know nothing about coding, don’t worry! You can start from the very basics. The first part of the course is ideal for beginners and people who want to brush up on their Python skills. And then, once you have covered the basics, you will be ready to tackle financial calculations and portfolio optimization tasks.   

Finance Fundamentals.  

And it gets even better! The Finance block of this course will teach you in-demand real-world skills employers are looking for. To be a high-paid programmer, you will have to specialize in a particular area of interest. In this course, you will focus on Finance, covering many tools and techniques used by finance professionals daily:  

Rate of return of stocks  

Risk of stocks  

Rate of return of stock portfolios  

Risk of stock portfolios  

Correlation between stocks  

Covariance  

Diversifiable and non-diversifiable risk  

Regression analysis  

Alpha and Beta coefficients  

Measuring a regression’s explanatory power with R^2  

Markowitz Efficient frontier calculation  

Capital asset pricing model  

Sharpe ratio  

Multivariate regression analysis  

Monte Carlo simulations  

Using Monte Carlo in a Corporate Finance context  

Derivatives and type of derivatives  

Applying the Black Scholes formula  

Using Monte Carlo for options pricing  

Using Monte Carlo for stock pricing

Everything is included! All these topics are first explained in theory and then applied in practice using Python.

Is there a better way to reinforce what you have learned in the first part of the course?  

This course is great, even if you are an experienced programmer, as we will teach you a great deal about the finance theory and mechanics you will need if you start working in a finance context.


10- Natural Language Processing with Deep Learning in Python

Complete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets

What you'll learn

Understand and implement word2vec
Understand the CBOW method in word2vec
Understand the skip-gram method in word2vec
Understand the negative sampling optimization in word2vec
Understand and implement GloVe using gradient descent and alternating least squares
Use recurrent neural networks for parts-of-speech tagging
Use recurrent neural networks for named entity recognition
Understand and implement recursive neural networks for sentiment analysis
Understand and implement recursive neural tensor networks for sentiment analysis

This course focuses on "how to build and understand", not just "how to use". Anyone can learn to use an API in 15 minutes after reading some documentation. It's not about "remembering facts", it's about "seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.

Who this course is for:

Students and professionals who want to create word vector representations for various NLP tasks
Students and professionals who are interested in state-of-the-art neural network architectures like recursive neural networks


So far more than 24 million students have enrolled in a Udemy course, whether it's to boost their job performance, develop their skill set, or just improve themselves personally. Each course offers instructor-created videos, slides, text, quizzes, tests, and other resources to enhance learning. Courses are provided on-demand, which allows students to enroll at their convenience and move at their own pace, without having to worry about deadlines. During the course, students can communicate directly with their instructor, asking questions, posting comments, and sharing feedback.

It's a win-win for course creators and students alike, and it's 100% free to create and host your course on Udemy.

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