7 Powerful Python Online Courses on Udemy

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 a 7 powerful 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:

  • Scraping data from nearly any website (including JavaScript-enabled sites)
  • 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

Join this course for FREE


Web Scraping with Python from Scratch

Gathering and processing data is now one of most vital and profitable fields. This Web Scraping course is meant for beginners; it is so easy and covers the fundamentals of Web Scraping with Python BeautifulSoup & Requests.

  • In this Web Scraping course, you will learn:
  • Installing Python Web Scraping libraries, BeautifulSoup & Requests.
  • Extracting URLs from a webpage.
  • Scraping text data from a webpage.
  • Crawling multiple webpages and scraping data from each of them.
  • Handling navigation links and move to next pages.
  • Saving scraped data into a CSV file.
  • Overview about other popular web scraping frameworks.

Join this course for FREE


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.

In this course, you will learn creating a web crawler in Scrapy, crawling a single or multiple websites and scrape data, deploying your spider, logging into websites with Scrapy, using Scrapy with Selenium in Special Cases, e.g. to Scrape JavaScript Driven web pages, exporting data extracted by Scrapy into CSV, XML, JSON, or Excel files, downloading images, storing data extracted by Scrapy into MySQL and MongoDB databases, and several real-life web scraping projects.

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.

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Web Scraping with Python: BeautifulSoup, Requests & Selenium

In this course, you will learn how to perform web scraping using Python 3 and the BeautifulSoup and Requests. You will also Selenium alongside Beautiful Soup to crawl AJAX & JavaScript driven pages.

This Web Scraping course covers the following topics:

  • Review of data structures (Lists, Dictionaries, Tuples, File Handling)
  • How websites are hosted on servers
  • Calls to the server (GET, POST methods)
  • Review of HTML and CSS
  • Requests Module and BeautifulSoup Module overview
  • Parsing HTML using BeautifulSoup
  • Filtering elements using BeautifulSoup and navigating the Parse Tree
  • JavaScript and AJAX overview
  • Selenium and the need for it
  • Selecting elements using Selenium
  • CSS selectors
  • XPath selectors
  • Navigating pages using Selenium
  • Practical Projects

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Chatbot Building: Rasa, DialogFlow & WIT.AI Bots with Python

Do you want to create a talking chatbot that interact with your visitors? In this tutorial, you will learn how to create Python chatbots using DialogFlow and Wit.AI platforms as well as powerful Rasa NLU and Rasa Core. DialogFlow, Wit.AI and Rasa provide several Natural Language Processing functions that parse user input and match them to the right response. Implementing NLP in your bot can be pretty difficult, but these platforms make it much easier to create a Facebook Messenger bot or a website chatbot.

This Python chatbot course will help you:

  • Build chatbots with Python using Rasa NLU & Rasa Core, DialogFlow and Wit.AI
  • Use DialogFlow to build a Facebook Messenger chatbot.
  • Use Wit.AI to build a Facebook Messenger chatbot.
  • Use Rasa NLU to build a chatbot.
  • Use Rasa Core to build a chatbot.
  • Understand intents and entities.
  • Build a Facebook Messenger bot.
  • Deploy chatbots to cloud platforms such as Heroku.

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Node.JS Professional? Check this course:

Chatbot Building: DialogFlow & Wit.AI Chatbots with Node.JS


Natural Language Processing (NLP) with Python NLTK

This Natural Language Processing (NLP) tutorial covers core basics of NLP using the well-known Python package Natural Language Toolkit (NLTK). The course helps trainees become familiar with common concepts like tokens, tokenization, stemming, lemmatization, and using regex for tokenization or for stemming. It discusses classification, tagging, normalization of our input or raw text. It also covers some machine learning algorithms such as Naive Bayes.

In this course, you will build several practical projects, inlucing, Gender Predictor, Document Classifier, Spell Checker, and Plagiarism Detector.

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Word2Vec Word Embeddings with TensorFlow

In this Word2Vec tutorial, you will learn how to train a Word2Vec Python model and use it to semantically suggest names based on one or even two given names.

Word2Vec is one of the most popular techniques to learn word embeddings using shallow neural network. Word2vec is a particularly computationally-efficient predictive model for learning word embeddings from raw text.

In this Word2Vec tutorial, you will learn The idea behind Word2Vec:

  • Take a 3 layer neural network. (1 input layer + 1 hidden layer + 1 output layer)
  • Feed it a word and train it to predict its neighbouring word.
  • Remove the last (output layer) and keep the input and hidden layer.
  • Now, input a word from within the vocabulary. The output given at the hidden layer is the ‘word embedding’ of the input word.

In this Word2Vec tutorial we are going to do all steps of building and training a Word2vec Python model (including pre-processing, tokenizing, batching, structuring the Word2Vec Python model and of course training it) using Python TensorFlow. Finally, we are going to use our trained Word2Vec Python model to semantically suggest names based on one or even two given names.

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Seize the opportunity and improve your skills today through these useful courses, and even click here to check more Python programming courses. Enjoy learning!


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