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Complete Data Science,Machine Learning,DL,NLP & Interview Mastery Bundle

Master the theory, practice,and math behind Data Science,Machine Learning,Deep Learning,NLP with end to end projects

What you'll learn

  • Master ML, NLP & Deep Learning: Build and deploy real-world machine learning and NLP models using tools like TensorFlow, PyTorch, and scikit-learn.

  • Hands-on Projects: Apply your skills through industry-grade projects in finance, healthcare, and e-commerce.

  • Strong Mathematical Foundation: Understand the math behind ML—linear algebra, calculus, probability, and more.

  • Advanced Topics: Learn deep learning, reinforcement learning, transformers, and MLOps.

  • Practical Coding Skills: From Python basics to advanced OOPs, data handling, SQL, APIs, and Flask web apps.

  • Data Engineering & Preprocessing: Work with real datasets, clean data, handle outliers, and engineer powerful features.

  • Model Optimization: Improve accuracy with hyperparameter tuning, model evaluation, and deployment techniques.

I am the Ex Co-founder and Chief AI Engineer of iNeuron and my experience is pioneering in machine learning, deep learning, and computer vision,Generative AI,an educator, and a mentor, with over 15 years’ experience in the industry. This is my Data Science Course where I explain various topics on machine learning, deep learning, and AI with many real-world problem scenarios. I have delivered over 30+ tech talks on data science, machine learning, and AI at various meet-ups, technical institutions, and community-arranged forums. My main aim is to make everyone familiar of ML and AI.

Getting started

Lecture 1- Welcome To The Course
Lecture 2-  Complete Materials
Lecture 3- Anaconda Installation
Lecture 4- Getting Started With VS Code

Lecture 1 – Getting Started With VS Code
Lecture 2 – Different Ways of Creating Virtual Environment
Lecture 3 – Solve Conda Not Recognized Issue
Lecture 4 – Python Basics – Syntax And Semantics
Lecture 5 – Variables In Python
Lecture 6 – Basics Data Types In Python
Lecture 7 – Operators In Python
Lecture 8 – Coding Exercise And Assignments

Lecture 1 – Conditional Statements (if, elif, else)
Lecture 2 – Loops In Python
Lecture 3 – Coding Exercise And Assignments

Lecture 1 – Conditional Statements (if, elif, else)
Lecture 2 – Loops In Python
Lecture 3 – Coding Exercise And Assignment

Lecture 1 – List And List Comprehension In Python
Lecture 2 – List Practice Code And Assignment
Lecture 3 – Tuple In Python
Lecture 4 – Tuple Assignment And Practise Code
Lecture 5 – Sets In Python
Lecture 6 – Sets Assignment and Practise Code
Lecture 7 – Dictionaries In Python
Lecture 8 – Dictionaries Assignments And Practise Questions
Lecture 9 – Real World Usecases Of List

Lecture 1 – Conditional Statements (if, elif, else)
Lecture 2 – Loops In Python
Lecture 3 – Coding Exercise And Assignment

Lecture 1 – List And List Comprehension In Python
Lecture 2 – List Practice Code And Assignment
Lecture 3 – Tuple In Python
Lecture 4 – Tuple Assignment And Practise Code
Lecture 5 – Sets In Python
Lecture 6 – Sets Assignment and Practise Code
Lecture 7 – Dictionaries In Python
Lecture 8 – Dictionaries Assignments And Practise Questions
Lecture 9 – Real World Usecases Of List

Lecture 1 – Celsius To Fahrenheit
Lecture 2 – Area of a Rectangle
Lecture 3 – Distance Covered by a Vehicle
Lecture 4 – Number of Rounds of Lift
Lecture 5 – Line Equation

Question 1 – Sum of List Elements
Question 2 – Largest Element in a List
Question 3 – Remove Duplicate in a List
Question 4 – Check if all elements in a List are Unique
Question 5 – Reverse a List
Question 6 – Number of Odd and Even Elements in a list
Question 7 – Check if List is Subset of Another List
Question 8 – Maximum Difference between 2 consecutive elements in a List
Question 9 – Merge two sorted List
Question 10 – Rotate a List
Question 11 – Merge 2 list into Dictionary
Question 12 – Merge Multiple Dictionary
Question 13 – Words Frequency in a Sentence
Question 14 – Palindromic Tuple
Question 15 – Merge Dictionaries with Common Keys

Question 1 – Sum of List Elements
Question 2 – Largest Element in a List
Question 3 – Remove Duplicate in a List
Question 4 – Check if all elements in a List are Unique
Question 5 – Reverse a List
Question 6 – Number of Odd and Even Elements in a list
Question 7 – Check if List is Subset of Another List
Question 8 – Maximum Difference between 2 consecutive elements in a List
Question 9 – Merge two sorted List
Question 10 – Rotate a List
Question 11 – Merge 2 list into Dictionary
Question 12 – Merge Multiple Dictionary
Question 13 – Words Frequency in a Sentence
Question 14 – Palindromic Tuple
Question 15 – Merge Dictionaries with Common Keys

Lecture 1 – File Operation In Python
Lecture 2 – Working With File Paths
Lecture 3 – File Handling Operation Assignment With Solutions

Lecture 1 – Exception Handling With try except else and finally blocks
Lecture 2 – Exception Handling Practise Assignments And Solution

OOps Concepts With Classes And Objects

Lecture 1 – Classes And Objects In Python
Lecture 2 – Classes And Objects Practise Questions And Solutions
Lecture 3 – Inheritance In OOPS
Lecture 4 – Polymorphism In OOPS
Lecture 5 – Encapsulation In OOPS
Lecture 6 – Abstraction In OOPS
Lecture 7 – Practise Assignments With Solutions
Lecture 8 – Magic Methods In Python
Lecture 9 – Operator Overloading In Python
Lecture 10 – Custom Exception Handling
Lecture 11 – Complete OOPS Practise Question With Solutions

Lecture 1 – Iterators In Python
Lecture 2 – Generators With Practical Implementation
Lecture 3 – Function Copy, Closures And Decorators
Lecture 4 – Advance Python Practise Questions And Solutions

Lecture 1 – Numpy In Python
Lecture 2 – Pandas – DataFrame And Series
Lecture 3 – Data Manipulation With Pandas And Numpy
Lecture 4 – Reading Data From Various Data Source Using Pandas
Lecture 5 – Data Visualization With Matplotlib
Lecture 6 – Data Visualization With Seaborn
Lecture 7 – Pandas And Numpy Assignments And Solutions

Lecture 1 – SQLITE3 Assignments And Solutions
Lecture 2 – CRUD Operation With SQLite3 And Python

Lecture 1 – Logging Practical Implementation In Python
Lecture 2 – Logging With Multiple Loggers
Lecture 3 – Logging With A Real World Example
Lecture 4 – Logging Assignments And Solutions

Lecture 1 – What Is Process And Threads
Lecture 2 – Multithreading Practical Implementation With Python
Lecture 3 – Multiprocessing Practical Implementation With Python
Lecture 4 – Thread Pool Executor and Process Pool
Lecture 5 – Implement Web Scraping Usecase With Multithreading
Lecture 6 – Real World Usecase Implementation With MultiProcessing

Lecture- 1 Memory Allocation And DeallocationGarbage collection and Best Practises

Lecture 1 – Introduction To Flask Framework
Lecture 2 – Understanding Simple Flask App Skeleton
Lecture 3 – Integrating HTML With Flask Web App
Lecture 4 – Working With HTTP Verbs Get And Post
Lecture 5 – Building Dynamic URL, Variables Rule And Jinja2 Template Engine
Lecture 6 – Working With REST APIs And HTTP Verbs PUT And DELETE

Lecture 1 – Building Web App Using Streamlit
Lecture 2 – Example Of ML App With Streamlit Web App

Lecture 1 – What is Statistics And its Application
Lecture 2 – Types Of Statistics
Lecture 3 – Population Vs Sample Data
Lecture 4 – Measure Of Central Tendency
Lecture 5 – Measure Of Dispersion
Lecture 6 – Why Sample Variance Is Divided By n-1?
Lecture 7 – Standard Deviation
Lecture 8 – What Are Variables?
Lecture 9 – What are Random Variables
Lecture 10 – Histograms – Descriptive Statistics
Lecture 11 – Percentile And Quartiles – Descriptive Statistics
Lecture 12 – 5 Number Summary – Descriptive Statistics
Lecture 13 – Correlation And Covariance

Download entite curriculam

Become Interview-Ready in 30 Days With

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  • Real-world projects and case studies.
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