Flask: 

• Explanation of Web APIs & RESTful APIs.
• Discussion on Flask & its usage.
• HTTP methods in Flask
• Implementing, Deploying & Consuming: Flask APIs.
• Debugging the application for troubleshooting.
• Developing a Real-time Flask Application/Capstone Project.
• Discussion of most asked interview questions on Flask.

Django:

• What is Django & its usage?
• What is a Web App?
• Learn the basics of HTML, CSS, JavaScript & jQuery.
• Installing Django application.
• What we’ll learn on Django:
  – Understanding the Django settings.
  – URLs and Web Server Gateway Interface (WSGI) management.
  – Explanation of Django application Skeleton (admin, apps, models, tests, views, migrations)
  – Creating views, templates, templates tags and inheriting.
  – Creating models, registering, migrating to DB, importing.
  – Mapping of URLs and URL patterns.
  – Admin interface to create users & connect models to DB.
  – MTV design pattern.
  – Static files, creating forms, injecting, inheriting.
  – Implementing HTTP methods for forms.
  – Validation and model forms.
• Deploying Django application & running it.
• Debugging the application for troubleshooting.
• Developing a real-time Django web application/Capstone project.
• Authentication & Authorization.
• Discussion of most asked interview questions on Django.

UNIT TESTING

• Writing unit-test cases,
• Explanation of unit-test library
• How to run unit-test cases?
• Test coverage.

VERSION CONTROL

• Learning Git & GitHub

DATABASE BASICS

• Understanding Relational Database
• SQL statements/clauses
• Views
• Functions
• Procedures
• Triggers
• Inner queries, Expressions
• Learn NoSQL Basics

DATA SCIENCE, ML/AI (Basics)

• Introduction to Data Science, ML/AI
• Exploring Numpy, Pandas, DataFrame
• Data visualization libraries (matplotlib, seaborn, plotly, cufflinks)
• Machine Learning models:
  – Linear Regression,
  – Logistic Regression,
  – K Nearest Neighbors (KNN),
  – Decision Trees, Radom Forest,
  – Principal Component Analysis (PCA),
  – Recommender System
• What is NLP? Natural Language Processing.
• Introduction to Deep Learning.
• What is Neural Networks?
• Interview preparation for data science.
• Most asked interview questions on AI/ML.