Python Zero to Hero [ Learn to Make Industry Level Project From Scratch ]

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LMT Team

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About the Course 0
Python Zero to Hero Covering Machine Learning and Web Development + [Capstone Project From Scratch ]
Learn to create Industry Level Capstone Project with Machine Learning and Web Development in Python and make yourself future ready
- 📚80+ video Lectures
- 👣 Beginner Friendly
- 📌 3 Mini Project in Python
- 📑 Assignment Based Learning
- 👨🏻‍💻 One Industry Level Project using Python | Machine Learning | Web Development
- 📄 Completion Certificate
- ⭐️ Trusted by 100+ Students
- 🔥 10 Lakh+ Video Views of Youtube
Course Sections:
- 💻 Python from Scratch
- 🗣 Machine Learning from Scratch
- 📊 Web Development using flask
- 👨🏻‍💻 One Industry Level Project using Python | Machine Learning | Web Development
The one-stop destination to Start your Machine Learning and Data Science Journey
So let's dive in - Enroll today, Learn the Fundamentals & get to work with your Dream Company
No items in this section
Python ~ Section 01 : Introduction And Getting The Right Tools! 1
- Lecture2.1
  
  1.1 Introduction and Installation 05 min
Python ~ Section 02 : Basic I/O, Operators & Using IDE 5
- Lecture3.1
  
  2.1 Numbers and Strings 07 min
- Lecture3.2
  
  2.2 Lists and Dictionaries 07 min
- Lecture3.3
  
  2.3 Assignment Operators 05 min
- Lecture3.4
  
  2.4 Development Environment 04 min
- Lecture3.5
  
  2.5 Visual Studio Code: [VS_Code] 07 min
Python ~ Section 03 : Conditional Statements & Looping ! 5
- Lecture4.1
  
  3.1 Conditional Statements 05 min
- Lecture4.2
  
  3.2 User Input 05 min
- Lecture4.3
  
  3.3 WHILE Loop 05 min
- Lecture4.4
  
  3.4 FOR Loop 03 min
- Lecture4.5
  
  3.5 FOR Loop: (Dictionary Enumeration) 05 min
Python ~ Section 04 : OOPS! Functions, Classes & Exception Handling 4
- Lecture5.1
  
  4.1 Functions 07 min
- Lecture5.2
  
  4.2 Class and Objects 04 min
- Lecture5.3
  
  4.3 Constructors 05 min
- Lecture5.4
  
  4.4 Exception handling 07 min
Python ~ Section 05 : Python Modules & Experiencing Jupyter ! 5
- Lecture6.1
  
  5.1 Modules 06 min
- Lecture6.2
  
  5.2 Statistics Module 04 min
- Lecture6.3
  
  5.3 CSV Module 08 min
- Lecture6.4
  
  5.4 PIP 04 min
- Lecture6.5
  
  5.5 Jupyter Note Book 07 min
Python ~ Section 06 : Tkinter, SQL in Python & File Management 3
- Lecture7.1
  
  6.1 SQLite 10 min
- Lecture7.2
  
  6.2 Tkinter 11 min
- Lecture7.3
  
  6.3 Making [.exe] in Python 08 min
Python Assignments 2
- Lecture8.1
  
  Assignment 1
- Lecture8.2
  
  Assignment 2
[Bonus] Python Hands-On Projects + Source Code 4
- Lecture9.1
  
  Rock Paper Scissor Python Game 13 min
- Lecture9.2
  
  Message Encode Decode in Python Project 15 min
- Lecture9.3
  
  Calculator in Python 25 min
- Lecture9.4
  
  Source Code of all 3 Projects
Machine Learning ~ Section 01 : Introduction & Supervised / Unsupervised Learning 3
- Lecture10.1
  
  1.1 Introduction 07 min
- Lecture10.2
  
  1.2 Types of Machine Learning 05 min
- Lecture10.3
  
  1.3 Different Supervised Learning Algorithms 06 min
Machine Learning ~ Section 02 : Regression [Models, Implementation] 13
- Lecture11.1
  
  2.1 Linear Regression Introduction 10 min
- Lecture11.2
  
  2.2 Linear Regression Mathematics 13 min
- Lecture11.3
  
  2.3 Linear Regression Implementation 13 min
- Lecture11.4
  
  2.4 Regression Using Karl Pearson Coefficient 05 min
- Lecture11.5
  
  2.5 Linear Regression using Karl Pearson Coefficient Implementation 06 min
- Lecture11.6
  
  2.6 Linear Regression Library Implementation 05 min
- Lecture11.7
  
  2.7 Loss Analysis Using MSE 08 min
- Lecture11.8
  
  2.8 Mean Squared Error 04 min
- Lecture11.9
  
  2.9 Goodness Of Fit. 10 min
- Lecture11.10
  
  2.10 R-Squared Implementation 03 min
- Lecture11.11
  
  2.11 R-Squared Using Karl Pearson Coefficient 05 min
- Lecture11.12
  
  2.12 R-Squared Using Karl Pearson 05 min
- Lecture11.13
  
  2.13 Library Implementation of Metrics 03 min
Machine Learning ~ Section 03 : Data Processing & Pandas 4
- Lecture12.1
  
  3.1 Loss Optimizer 09 min
- Lecture12.2
  
  3.2 Gradient Descent Implementation 09 min
- Lecture12.3
  
  3.3 Data Processing Using Pandas 11 min
- Lecture12.4
  
  3.4 Train Test Split 06 min
Machine Learning ~ Section 04 : Classification, Score Analysis & [Bonus] Google Colabration 9
- Lecture13.1
  
  4.1 Classification Models 08 min
- Lecture13.2
  
  4.2 Logistic Regression 05 min
- Lecture13.3
  
  4.3 Loss For Classification Models 03 min
- Lecture13.4
  
  4.4 Log Loss Implementation 07 min
- Lecture13.5
  
  4.5 Score Analysis Basics 05 min
- Lecture13.6
  
  4.6 Confusion Matrix Implementation 08 min
- Lecture13.7
  
  4.7 Precision & Recall 07 min
- Lecture13.8
  
  4.8 F1 Score 05 min
- Lecture13.9
  
  [Bonus] Google Colabration 09 min
Machine Learning ~ Section 05 : K-Means Clustering, Decision Tree Classifier, Support Vector Information 6
- Lecture14.1
  
  5.1 K-Nearest neighbors 08 min
- Lecture14.2
  
  5.2 Iris 10 min
- Lecture14.3
  
  5.3 Support Vector Machine 10 min
- Lecture14.4
  
  5.4 Decision Tree Classifier 06 min
- Lecture14.5
  
  5.5 Digit Classification 08 min
- Lecture14.6
  
  5.6 K-Means Clustering 13 min
Machine Learning Assignment 5
- Lecture15.1
  
  Assignment 1
- Lecture15.2
  
  Assignment 2
- Lecture15.3
  
  Assignment 3
- Lecture15.4
  
  Assignment 4
- Lecture15.5
  
  Assignment 5
Web Development ~ Section 01 : Flask Introduction 2
- Lecture16.1
  
  1.1 Introduction And Installation 02 min
- Lecture16.2
  
  1.2 Boilerplate Code 05 min
Web Development ~ Section 02 : Routing & Redirecting 2
- Lecture17.1
  
  2.1 Routing 06 min
- Lecture17.2
  
  2.2 Redirecting 07 min
Web Development ~ Section 03 : Templating, Forms & Making API's With CRUD DB Operations 17
- Lecture18.1
  
  3.1 Template Prerequisites 12 min
- Lecture18.2
  
  3.2 Bootstrap 12 min
- Lecture18.3
  
  3.3 Flask File Hierarchy 06 min
- Lecture18.4
  
  3.4 Rendering Template 05 min
- Lecture18.5
  
  3.5 Jinja Templating 05 min
- Lecture18.6
  
  3.6 Conditions in Jinja 07 min
- Lecture18.7
  
  3.7 Enumeration In Jinja 04 min
- Lecture18.8
  
  3.8 Static Directory 06 min
- Lecture18.9
  
  3.9 Methods 05 min
- Lecture18.10
  
  3.10 Requests 06 min
- Lecture18.11
  
  3.11 Flash 10 min
- Lecture18.12
  
  3.12 Forms-Phase-1 09 min
- Lecture18.13
  
  3.13 Forms-Phase-2 07 min
- Lecture18.14
  
  3.14 Forms-Phase-3 10 min
- Lecture18.15
  
  3.15 Forms-Phase-4 11 min
- Lecture18.16
  
  3.16 Forms-Phase-5 06 min
- Lecture18.17
  
  3.17 Forms-Phase-6 12 min
Hands-On : Capstone Project + Source Code 3
- Lecture19.1
  
  Phase1 Model-1 26 min
- Lecture19.2
  
  Phase2 Front-End 15 min
- Lecture19.3
  
  Phase3 Back-End 18 min

Python Zero to Hero Covering Machine Learning and Web Development + [Capstone Project From Scratch ]

Learn to create Industry Level Capstone Project with Machine Learning and Web Development in Python
and make yourself future ready

📚80+ video Lectures
👣 Beginner Friendly
📌 3 Mini Project in Python
📑 Assignment Based Learning
👨🏻‍💻 One Industry Level Project using Python | Machine Learning | Web Development
📄 Completion Certificate
⭐️ Trusted by 100+ Students
🔥 10 Lakh+ Video Views of Youtube

Course Sections:

💻 Python from Scratch
🗣 Machine Learning from Scratch
📊 Web Development using flask
👨🏻‍💻 One Industry Level Project using Python | Machine Learning | Web Development

The one-stop destination to Start your Machine Learning and Data Science Journey

So let’s dive in – Enroll today, Crack the exam & get to work with your Dream Company

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Python Zero to Hero Covering Web Development and Machine Learning + [Capstone Project From Scratch Included] + Mentorship

Build a complete understanding of Python from the ground up! Learn to use Python professionally, learning both Python 2 and Python 3!

Course Provider: Organization

Editor's Rating:
5

Course Features

Lectures 93
Quizzes 0
Duration 12 Hours
Skill level All levels
Language English
Students 18
Certificate Yes
Assessments Yes

LMT Team

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akashnkumar1
Awesome 1:1 Mentorship program

I have an enjoyable learning experience at Last Moment Tuition, and The course contents are well organized also it gets a lot easier when you watch the tutorial and code it right then and there. The best part I felt about LMT is that the whole team keeps you record and always pushing you so that you keep learning and get closer to your goal. They really do care about helping you. 😊