Python Language(AI)

Experience the need & intuition of language features from machine learning and project driven perspective. Get the self-confidence to code any machine learning, deep learning and math logics in python by working on real python mini projects.

  • 3200
  • Course Includes
  • 20+ hrs of videos with experiences of Language Features
  • Weekly LIVE support for doubts, assignments and projects
  • 5 Quality Mini-Projects
  • Restricted to single user
  • Validity for 3 months

What You Learn

  • Experiential knowledge of python language features without byheart of syntaxes
  • How to crack tricky python puzzles in Interview & Test with Ease
  • Understanding data structures in python & how to apply them on real problems
  • Mastery of 3 styles of programming: Procedural, ObjectOriented & Functional
  • Mastery of advanced Datastructures used in data science projects: ND Array(numpy) & DataFrame(pandas)
  • How to build real software using python with help of Quality Projects

Target Audience

  • Anybody in this world who wants to express ideas/logics to computing machines with python
  • People who wants to do AI/ML/DL/DataScience Work
  • People who wants to crack ML python Interview & Test
  • Prerequisites: Discipline, Passion/Necessity

Course Description

Python got very wide acceptance among the AI community for any type of data science work. The Python Language for AI Course aims for an experiential and joyful journey with the goal of building AI software with confidence. We take an experiential approach with the following key ideas for this course:

1) People get messed up in language learning by properly byhearting the syntaxes and syntax examples without knowing the essence of features. In this course, we do not encourage syntax to byheart by any means and instead, make you realize the intent of the feature with practical experiences.

2) People learn a language with approaches like note writing, studying the theory of each feature with an example and think that they know the language. You know the language better and start enjoying the language only when you start developing projects with what you learned. In this course, we provide a series of useful projects that makes you experience the joy of software building.

3) Most people byheart FAQs to clear job tests/interviews. By luck, even if u get a job, you feel a nightmare in writing real software. In this course, you are given assignments or interview questions for each topic after you have a practical understanding of the topic. You should able to think logically and solve those questions. This gives you an enormous self-confidence in job interviews and also real software development in a company.

The course covers the following topics in-depth:

Course Content

Framework for Language Learning   12 Min
Curriculum for Language Learning   16 Min
Why Python?   9 Min
Environment Setup   14 Min
Jupyter Classic Notebook vs Jupyter Lab Notebook   11 Min
Working with jupyter lab   11 Min
Working with spyder   6 Min
Language Basics || Interview Questions  
Overview of Types   8 Min
Primitive Types   9 Min
Operations of Primitive Types   20 Min
Custom Types   9 Min
Type Casting   7 Min
Static vs Dynamic Typing   8 Min
Download Code  
Overview of Programming Styles   5 Min
Overview of Procedural Style   5 Min
Control Statements   18 Min
Need of Functions   9 Min
Functions with Optional Arguments   8 Min
Functions with Testability   6 Min
Download Code  
Type System & Procedural Programming Style || Interview Questions  
Writing Variable Argument Functions   12 Min
Download Code  
Overview of Data Structures   6 Min
List Overview   4 Min
Working with List   24 Min
List Applications in Python   15 Min
Download Code  
Working with Tuple   8 Min
Download Code  
List & Tuple Data Structures || Interview Questions  
Stack & Queue Overview   3 Min
Working with Stack & Queue   13 Min
Stack & Queue Applications in Python   9 Min
Download Code  
Set Overview   3 Min
Working with Set   19 Min
Set Applications in Python   6 Min
Download Code  
Dictionary Overview   3 Min
Working with Dictionary   13 Min
Dictionary Applications in Python   10 Min
Download Code  
Set & Dictionary Data Structures || Interview Questions  
Overview of 1D-Array   3 Min
Need of Numpy Array   18 Min
Basic Operations of Numpy Array   23 Min
Broadcasting & Vectorization in Depth   15 Min
Vectorized Aggregate Operations   7 Min
Vectorized Relational Operations   10 Min
Download Code  
Overview of 2D-Array   4 Min
Creation & Operations   18 Min
Vectorized Operations   14 Min
Download Code  
Numpy Array Data Structure || Interview Questions  
Overview of Tensor   3 Min
Working with Tensors   9 Min
Download Code  
Overview of Data Frames   4 Min
Series   25 Min
Dataframe Basics   36 Min
Aggregates & Grouping   20 Min
Combining Dataframes   22 Min
Reshape & Sorting   18 Min
Download Code  
Data Frame Data Structure || Interview Questions  
Overview of Object Oriented Style   11 Min
Overview of Encapsulation, Datahiding   5 Min
Experience with Encapsulation - Procedural Style   17 Min
Experience with Encapsulation - OO style   14 Min
Overview of Polymorphism, Dynamic Binding   8 Min
Experience with Polymorphism - Procedural Style   6 Min
Experience with Polymorphism - OO Style   9 Min
Download Code  
Overview of Reuse   5 Min
Experience with Reuse - Inheritance I   11 Min
Experience with Reuse - Inheritance II   14 Min
Experience with Reuse - Inheritance III   11 Min
Experience with Reuse - Composition   19 Min
Overview of Modeling   4 Min
Experience with Modeling - Procedural Style   17 Min
Experience with Modeling - OO Style   9 Min
Download Code  
Object Oriented Style || Interview Questions  
Overview of Functional Programming   10 Min
Pure Functions   14 Min
Functions as Type   22 Min
Declarative Programming-I   11 Min
Declarative Programming-II   11 Min
Declarative Programming-III   10 Min
Performance Optimization-I   11 Min
Performance Optimization-II   14 Min
Debugging and Testing Pure Functions   8 Min
Download Code  
Functional Programming Style || Interview Questions  
Programming Styles || Interview Questions  
Overview of Modularity   4 Min
Python Files as Modules   12 Min
Organizing Modules   7 Min
Importing Modules   6 Min
Exploring Modules   10 Min
Download Code  
Using Random Generators   12 Min
Download Code  
Overview of exception handling   3 Min
Need of exception handling   11 Min
Working with Try & Except blocks   12 Min
Working with Finally block   9 Min
Custom Exceptions   12 Min
Download Code  
File IO || Interview Questions  
Need of Data Streaming   7 Min
Object Oriented Iterators in Python   13:06 Min
Lazy Evaluation of Iterators   6 Min
Internals of Object Oriented Iterators   10 Min
Functional Iterators or Generators - I   12 Min
Functional Iterators or Generators-II   9 Min
Out of Box Functional Iterators   24:48 Min
Download code  
Data Streaming || Interview Questions  
Password File Cracker  
Document Search Engine  
Currency Converter  
YouTube Stats Scraper  
Facebook Friend Recommender  
Lifecycle of Compiled Programs   23 Min
Experience Compiled Program Lifecycle   10 Min
Lifecycle of Interpreted Programs   20 Min
Experience Interpreted Program Lifecycle   4 Min
Lifecycle of Hybrid(Compiled+Interpreted) Programs   16 Min
Experience Hybrid(Compiled+Interpreted) Program Lifecycle   5 Min
Virtual Machines with JIT Compiler   15 Min
Static Linking   16 Min
Experience Static Linking   14 Min
Dynamic Linking   6 Min
Experience Dynamic Linking   12 Min
Summary of Static & Dynamic Linking   4 Min
Debugging with Jupyter   10 Min
Profiling with Jupyter   13 Min
Download Code  

About the Guru


ThimmaReddy is the founder of Algorithmica and  holds Master Degree from IIT-Guwahati. He believes that education means training of the mind to think and solve problems with direct experience. Prior to founding Algorithmica, ThimmaReddy worked at LSI Logic, Agami Systems, Applied Discovery & some other startups as an Engineer, Architect & AI Strategist. He strongly asserts that the current education system is outdated & needs complete overhaul to upbring the people to solve the problems posed by companies & research.

To get guranteed success in any area of skill, he advocates three needed things: scienitifc curriculum, experiential learning & mentorship. At Algorithmica, he transformed thousands of students and working professionals to quality thinkers and he also created different scientifc curriculum for different pressing problems faced by students, working professionals and companies. ThimmaReddy loves to explore every aspect of computing field and is very passionate to share his experiential knowledge too.

His Alumni works in top-notch companies like Google, Mircosoft, Facebook, Amazon, Uber, WallMart Labs, LinkedIn, Twitter, etc., spread around the world. He is now acting as mentor for some startup AI companies and in parallel leading algorithmica for THE ultimate destination for quality experiential learning in whole computational field/domain.