Python Zero to Hero: [Web+ML]+ Mentorship

Teacher

Raunak Joshi

Categories

All-Courses, Courses, Mumbai University, Placement Preparation, Programming Language, python+aptitude, upgrade-placement

Review

(1 review)

₹15,000.00 ₹7,999.00

Introduction to the Course (Must watch before you Start) 1
- Lecture1.1
  
  Welcome to the Course 04 min
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
[Bonus] Python Hands-On Projects + Source Code 4
- Lecture8.1
  
  Rock Paper Scissor Python Game 13 min
- Lecture8.2
  
  Message Encode Decode in Python Project 15 min
- Lecture8.3
  
  Calculator in Python 25 min
- Lecture8.4
  
  Source Code of all 3 Projects
Machine Learning ~ Section 01 : Introduction & Supervised / Unsupervised Learning 3
- Lecture9.1
  
  1.1 Introduction 07 min
- Lecture9.2
  
  1.2 Types of Machine Learning 05 min
- Lecture9.3
  
  1.3 Different Supervised Learning Algorithms 06 min
Machine Learning ~ Section 02 : Regression [Models, Implementation] 13
- Lecture10.1
  
  2.1 Linear Regression Introduction 10 min
- Lecture10.2
  
  2.2 Linear Regression Mathematics 13 min
- Lecture10.3
  
  2.3 Linear Regression Implementation 13 min
- Lecture10.4
  
  2.4 Regression Using Karl Pearson Coefficient 05 min
- Lecture10.5
  
  2.5 Linear Regression using Karl Pearson Coefficient Implementation 06 min
- Lecture10.6
  
  2.6 Linear Regression Library Implementation 05 min
- Lecture10.7
  
  2.7 Loss Analysis Using MSE 08 min
- Lecture10.8
  
  2.8 Mean Squared Error 04 min
- Lecture10.9
  
  2.9 Goodness Of Fit. 10 min
- Lecture10.10
  
  2.10 R-Squared Implementation 03 min
- Lecture10.11
  
  2.11 R-Squared Using Karl Pearson Coefficient 05 min
- Lecture10.12
  
  2.12 R-Squared Using Karl Pearson 05 min
- Lecture10.13
  
  2.13 Library Implementation of Metrics 03 min
Machine Learning ~ Section 03 : Data Processing & Pandas 4
- Lecture11.1
  
  3.1 Loss Optimizer 09 min
- Lecture11.2
  
  3.2 Gradient Descent Implementation 09 min
- Lecture11.3
  
  3.3 Data Processing Using Pandas 11 min
- Lecture11.4
  
  3.4 Train Test Split 06 min
Machine Learning ~ Section 04 : Classification, Score Analysis & [Bonus] Google Colabration 9
- Lecture12.1
  
  4.1 Classification Models 08 min
- Lecture12.2
  
  4.2 Logistic Regression 05 min
- Lecture12.3
  
  4.3 Loss For Classification Models 03 min
- Lecture12.4
  
  4.4 Log Loss Implementation 07 min
- Lecture12.5
  
  4.5 Score Analysis Basics 05 min
- Lecture12.6
  
  4.6 Confusion Matrix Implementation 08 min
- Lecture12.7
  
  4.7 Precision & Recall 07 min
- Lecture12.8
  
  4.8 F1 Score 05 min
- Lecture12.9
  
  [Bonus] Google Colabration 09 min
Machine Learning ~ Section 05 : K-Means Clustering, Decision Tree Classifier, Support Vector Information 6
- Lecture13.1
  
  5.1 K-Nearest neighbors 08 min
- Lecture13.2
  
  5.2 Iris 10 min
- Lecture13.3
  
  5.3 Support Vector Machine 10 min
- Lecture13.4
  
  5.4 Decision Tree Classifier 06 min
- Lecture13.5
  
  5.5 Digit Classification 08 min
- Lecture13.6
  
  5.6 K-Means Clustering 13 min
Web Development ~ Section 01 : Flask Introduction 2
- Lecture14.1
  
  1.1 Introduction And Installation 02 min
- Lecture14.2
  
  1.2 Boilerplate Code 05 min
Web Development ~ Section 02 : Routing & Redirecting 2
- Lecture15.1
  
  2.1 Routing 06 min
- Lecture15.2
  
  2.2 Redirecting 07 min
Web Development ~ Section 03 : Templating, Forms & Making API's With CRUD DB Operations 17
- Lecture16.1
  
  3.1 Template Prerequisites 12 min
- Lecture16.2
  
  3.2 Bootstrap 12 min
- Lecture16.3
  
  3.3 Flask File Hierarchy 06 min
- Lecture16.4
  
  3.4 Rendering Template 05 min
- Lecture16.5
  
  3.5 Jinja Templating 05 min
- Lecture16.6
  
  3.6 Conditions in Jinja 07 min
- Lecture16.7
  
  3.7 Enumeration In Jinja 04 min
- Lecture16.8
  
  3.8 Static Directory 06 min
- Lecture16.9
  
  3.9 Methods 05 min
- Lecture16.10
  
  3.10 Requests 06 min
- Lecture16.11
  
  3.11 Flash 10 min
- Lecture16.12
  
  3.12 Forms-Phase-1 09 min
- Lecture16.13
  
  3.13 Forms-Phase-2 07 min
- Lecture16.14
  
  3.14 Forms-Phase-3 10 min
- Lecture16.15
  
  3.15 Forms-Phase-4 11 min
- Lecture16.16
  
  3.16 Forms-Phase-5 06 min
- Lecture16.17
  
  3.17 Forms-Phase-6 12 min
Hands-On : Capstone Project + Source Code 3
- Lecture17.1
  
  Phase1 Model-1 26 min
- Lecture17.2
  
  Phase2 Front-End 15 min
- Lecture17.3
  
  Phase3 Back-End 18 min

Python Zero to Hero Covering Web Development and Machine Learning + [Capstone Project From Scratch Included] + Mentorship [ Batch Starts from 1st week of April ]

One of the most exclusive courses available at last moment tuitions

Features of this program:
1. You will be given access to pre-recorded videos.
2. You will be attending 8 live zoom/meet sessions with the teacher(1 Session/week).
3. You will be assigned a special mentor who will help you with your doubts daily on WhatsApp/Call.
4. You will be developing 3 mini-projects using python and 1 industrial level project using python + machine learning + flask throughout the whole program.
5. You will get a certificate on completion of this program.
6. The very second batch will consist of only 10 students and students will be selected on a first come first serve basis.

The last date to enroll for the second batch is 31st March 2021
This program will be starting in the first week of April 2021

The price for this program is Rs. 16,000 but currently, 50% is going on so Sale Price is Rs. 7999

For further doubts and queries ask your question at the bottom of this form else contact us at:7038604912

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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 87
Quizzes 0
Duration 12 Hours
Skill level All levels
Language English
Students 8
Certificate Yes
Assessments Yes

Raunak Joshi

Reviews

Average Rating

1 rating

Detailed Rating

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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. 😊