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Road to AI Developer

Instructor led best course for beginners to make career in AI development as Data Engineer or AI Engineer.

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4.7

Rating

60 Hrs

Duration

Beginner

Level

55

Learners

What you'll learn

Expert level python programming for developing custom libraries and backend development
Overview of Machine learning, Deep learning and Natural language processing
ML ops techniques for deploying ML models in production at scale using AWS

Who should take this course

Ideal for beginners to start career in AI and Machine learning as Data engineer or AI engineer
Anyone can join, no prior knowledge in programming and AI is required

Skills you'll gain

Advanced Python programming
Recursive functions
Oops
Decorators
Backend development
Memory management
Unit testing
Multi-threading
Multi processing
Machine learning
Deep learning
NLP
Model Inferencing
API
Micro service
Docker
Data pipelines
AWS

Course contents

Python Origin, Where it is used and comparison with other programming languages.

Vanila Installation
Anaconda Installation
Miniforge Installation

In command window also in IDE like Jupyter notebook and VS code.

Built-in data types
Variable assignment
Additional data types

Arithmetic operators
Assignment operators
Comparison operators
Logical operators
Identity operators
Membership operators
Bitwise operators

Slicing, modifying, concatenating and formating strings
Practical assignment

Access, update, add and remove list items
Copy, join and sort list
Practical assignment

Using "if then else" and "match"
Practical assignment

Using "for" and "while" loop
Practical assignment

Reading and writing txt, csv, excel and Json file
Practical assignment

User defined function
Lambda function
Practical assignment

Exception handling using "try"..."except"
Practical assignment

Applying regex function like findall, search, split and sub
Practical assignment

Applying regex function like findall, search, split and sub
Practical assignment

Applying python's inbulit math function to perform mathematical tasks on numbers
Practical assignment

Why tuple and various tuple operation
Practical assignment

Why set and various set operation
Practical assignment

Why dict and various dict operation
Practical assignment

Creating multi domentional array
Performing various array operations
Mathemetical operations using array
Practical assignment

Creating data frame
Performing various data frame operations
Exploratory data analysis and data manipulation
Practical assignment

Creating date objects using differnt formats
Practical assignment

How to create class and objects
Basics of object oriented programming using class
Practical assignment

Creating visualization using matplotlib, plotly
Practical assignment

Creating python based REST api
Practical assignment

Basic overview of Scikit Learn and Scipy library
Practical assignment

List comprehension
Dictionary comprehension

*args and **kwargs

filter, map and reduce

Benefits and sImplementation using an example

Counter
defaultdict
deque
namedtuple
OrderedDict
ChainMap

Complex pattern matching
ID extraction

Encapsulation
Inheritance
Polymorphism
Abstraction

Benefits
Implementation using an example

Benefits
Implementation using an example

Steps to create packages

Web backend development using flask and MySQL

Memory management
Deep copy
Shallow copy

Unitest and Pytest

Concurrency
Global Interpreter Lock
Synchronization

Processes
Inter-process communication
Synchronization

Types of ML
Application areas
Python libraries

Overview
Application areas
Python libraries

Neural network concepts
Application areas
Python libraries

Creating rest API for ML model inferencing

Building micro service in python using flask
Deploying micro services in prod

Using Kubeflow pipelines

Using Airflow

AI Agents for beginners

This course will focus on understanding AI agents and how to use them create persona to perform complex, multi-step actions and make decisions independently.

LLM RAG for beginners

This course includes how to uses LLM and prompt engineering for question answering, reasoning, text summarization ect. Also allowing LLM to access knowledge from external sources using RAG.

Machine Learning for beginners

This Module allows user to create a digital twin for any document(e.g pdf, word).