With online courses, you can study anywhere, at the time suitable for you, get full lifetime access, and a Certificate of Completion. It is a wonderful experience that enables you to be taught by international skillful instructors whom you might not get the chance to meet otherwise. Nowadays, e-learning is a great advantage of technology that enables you to easily improve your skills and enjoy the learning experience.
In this article, we are trying to recommend the 9 best Python courses currently available on Udemy, the prominent online courses platform.
30 Days of Python | Unlock your Python Potential
The goal of this course is to enable you to learn Python by building real-world projects step-by-step while explaining every concept along the way. In only 30 days, you can learn the following topics:
- Building your own Python applications for all types of automation
- Sending emails & SMS text messages to your friends our your customers
- Reading and writing CSV, aka comma separated values, files to better store your data locally and work in popular programs like Microsoft Excel and Apple Numbers
- Understanding the basics behind the Python programming language so you’re ready to build more advanced projects like Web Applications
Complete Python Bootcamp: Go from zero to hero in Python
It is the “Best Seller” course under the “Python” topic. With 12.5 hours on-demand video, 17 Articles, over 100 lectures, more than 220,000 enrolled students, and overall rating 4.5, the course is the first choice of many of those who want to learn Python.
This course will teach you Python in a practical manner, with every lecture comes a full coding screencast and a corresponding code file.
It discusses the following topics in detail: Python Setup, Python Object and Data Structure Basics, Python Comparison Operators, Python Statements, Methods and Functions,, Object Oriented Programming, Errors and Exceptions Handling, Modules and Packages, Built-in Functions, Python Decorators, Python Generators, Advanced Python Modules, Advanced Python Objects and Data Structures, and several practical projects.
The Python Mega Course: Build 10 Real World Applications
The course starts by teaching Python basics for beginners and can serve as a refresher crash course for post-beginner students. After completing the first 5%, you will be guided in building 10 real life applications written in Python 3 in a wide range of areas that include: web applications, desktop applications, database applications, web scraping, web mapping, data analysis, interactive web visualization, computer vision for image and video processing, and object oriented programming.
Amazingly, the course consists of 23.5 hours on-demand video, 55 Articles, 44 Supplemental Resources, and 17 Coding exercises.
Python and Django Full Stack Web Developer Bootcamp
The course consists of 32 hours on-demand video, and it is the “Best Seller” under the “Django” topic.
REST APIs with Flask and Python
This course teaches you how to build professional REST APIs with Python, Flask, Flask-RESTful, and Flask-SQLAlchemy.
After taking this course, you will be able to create resource-based, production-ready REST APIs using Flask and popular extensions; use SQLAlchemy to easily and efficiently store resources to a database; and understand the complex intricacies of deployments and performance of REST APIs.
This course does a great job of covering everything you need to know to start building RESTful APIs using Python and Flask, which also includes testing your API endpoints, using a database, deployment and hosting.
This course covers not only the basics for building APIs in Flask but also real deployment, JWTs, SSL, git, NGINX and SQLAlchemy. That makes the information immediately useful. There is no need to figure out how to apply what you’ve just learned. The instruction is clear and concise. It is certainly one of the better courses here.
Students find it is an amazing and well designed course, totally applicable to real world APIs you need to build, and that the instructor is very clear in his lectures and provides very good support for any question you may have.
Scrapy: Powerful Web Scraping & Crawling with Python
Scrapy is a free and open source web crawling framework, written in Python. Scrapy is useful for web scraping and extracting structured data which can be used for a wide range of useful applications, like data mining, and information processing.
The course consists of more than 8 hours of on-demand video and more than 30 downloadable source code files.
If you are serious about learning scrapy then you should definitely take this course. This course explains everything you need to become a web scraping expert. Also, if you face a problem your questions are answered very fast by instructor himself.
Python Network Programming – Build 7 Python Apps
With this course, you can start automating network tasks using Python. This hands-on Python Network Programming training takes you from “Hello World!” to complex network applications in less than 15 hours. It is marked as the “Best Seller” course in the “Networking” topic.
During this course you will learn Python concepts which are relevant to your networking job and build some amazing network tools using Python, including Subnet calculator, configuring multiple network devices concurrently via SSH or Telnet, DHCP client simulator for testing a DHCP server in the local network, collecting information from routers and storing it in a MySQL database, OSPF network discovery via SNMP. Building the OSPF topology, basic network sniffer, and configuration file comparator.
Automated Software Testing with Python
This course will cover every fundamental testing skill that you need to know in order to get a job testing or apply these skills in your existing projects.
In this course, you will learn how to write automated unit and integration tests for all sorts of Python applications, use mocking and patching, write system tests using Python and Postman, set up a continuous integration pipeline using Travis CI, and write acceptance tests using Behave and Selenium.
In this course, the instructor covers how to write unit, integration, and systems test for a REST API. The course is well structured and easy to follow. The code is clear, concise, and easy to refactor to suit your own project needs. The last three parts of the course cover some advanced topics. Section 8 deals with writing automated tests in Postman; if you are working on a REST API project, you will find this information helpful. Section 9 covers the use of Travis CI for automated testing of your GitHub repositories on every push. Finally, section 10 demonstrates the use of Selenium for acceptance testing.
Overall, students find the course to be highly informative. After taking it, you will be able to write, with relative ease, unit, integration, and system tests for web apps, achieving 100% test coverage.
Machine Learning A-Z™: Hands-On Python & R In Data Science
It is the “Best Seller” course under the “Data Science” topic. With 40.5 hours on-demand video, 19 Articles, over 270 lectures, approx. 200,000 enrolled students, and overall rating 4.5, the course is a great choice for those who want to learn Machine Learning.
The course will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. 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.
It covers the following topics: Data Preprocessing, Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression, Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification, Clustering: K-Means, Hierarchical Clustering, Association Rule Learning: Apriori, Eclat, Reinforcement Learning: Upper Confidence Bound, Thompson Sampling, Natural Language Processing: Bag-of-words model and algorithms for NLP, Deep Learning: Artificial Neural Networks, Convolutional Neural Networks, Dimensionality Reduction: PCA, LDA, Kernel PCA, Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost.
Seize the opportunity and improve your skills today through these useful courses, and even click here to check more Python programming courses. Enjoy learning!