Full stack web development and AI with Python (Django)

HTML, CSS, JavaScript, Python, Django, Pandas, Sklearn, Keras, Git, Linux - Full stack web development /data science/ AI
4.59 (1659 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Full stack web development and AI with Python (Django)
11 263
students
39.5 hours
content
Jul 2020
last update
$94.99
regular price

What you will learn

Full stack web development through learning:

HTML to create websites

CSS and Bootstrap to style your websites

JavaScript - one of the most in demand coding languages in the market for web development

jQuery - a simplified way of applying Javascript

Python, an extremely valuable, versatile and powerful coding language

Django - the python framework for creating dynamic websites that can even integrate machine learning and AI

Create dynamic websites using the Model-View-Controller software design pattern

Data science - the ability to handle, clean, visualise and analyse big data. Some of the biggest salaries and investments go into Data Scientists (NumPy, Pandas, Sklearn, Matplotlib, Seaborn)

Full training in entry mathematics and statistics with a heavy emphasis on machine learning

How to develop machine learning from scratch - training algorithms using big data that can then be used in production for making predictions

Deep learning / AI - learn to create your own AI solutions, such as image classifiers, AI capable of creating art, and much more

Create a range of cutting edge neural network architectures

Document your code at a UK industry standard

Use AWS tools such as EC2 to host your websites

Integrate web server tools such as Nginx and Gunicorn

Master essential developer tools such as GIT, Jupyter notebook, Google Colab, GPUs, Putty, Browser Developer Tools

Gain experience in digital security - the DOs and DONTs of developing and scaling online websites and services

Harness the power of Linux

Create Application Programming Interfaces (APIs) in Python

Gain the ability to access machines (e.g. computers) remotely using SSH

Professional training in developing problem solving skills

Develop a broad portfolio of projects you can showcase to any employer

Gain the ability to adapt to any coding language with the concepts of Python

Where to find machine learning computing power for free

Master intermediate Python concepts such as object oriented programming and functional programming

Create, maintain and post a range of databases within your websites

Course Gallery

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Screenshot 4Full stack web development and AI with Python (Django)

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Our Verdict

Full Stack Web Development and AI with Python (Django) provides a comprehensive overview of full stack web development, data science, and AI concepts. The course is well-suited for students with prior programming knowledge who are looking to integrate their skills and build Proof of Concept Data Science Products. While there are some challenges, including the fast pace of certain sections and limited guidance on AWS deployment, overall this course offers valuable insights into the intersection of web development and AI.

What We Liked

  • Comprehensive full stack web development course covering HTML, CSS, JavaScript, Python, Django and more
  • Highly experienced instructor with expertise in mathematical and artificial intelligence concepts
  • Hands-on learning approach emphasized through practical exercises and projects
  • Covers a wide range of topics from front-end to back-end Python basics and machine learning
  • Projects focus on real-world applications, providing valuable experience for job seekers

Potential Drawbacks

  • Course may be challenging for beginners as some concepts are not fully explained
  • Some students have reported difficulties following along with the HTML and CSS lessons
  • Section 12 on Django has a fast pace that may be difficult for some students to keep up with
  • Limited guidance on deploying machine learning applications onto AWS or using Docker
2389518
udemy ID
29/05/2019
course created date
20/11/2019
course indexed date
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