Python and Machine Learning Training Course

Learn Python and Machine Learning from beginner to advanced level (Python Programming, Tkinter, Turtle, Django, Pandas, NumPy, Matplotlib, Scikit Learn, PyTorch, etc.)

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Python and Machine Learning Training Course

Join the Python and Machine Learning Training Course to become an expert in Python and Machine Learning. A few points about the complete training course:

  • Python and Machine Learning from beginner to advanced level
  • It Covers Machine learning, Python basics, Tkinter, Turtle, Django, Pandas, NumPy, Matplotlib, Scikit learn, PyTorch, TensorFlow, etc.
  • 50 modules
  • 60+ Hours of HD Video Course
  • Lifetime access
  • Weekly doubt clear sessions (Live)
  • Course Materials in PDFs, Source Code, etc.
  • Special job interview preparation tips
  • Exclusive Facebook Group Acces


Your Instructor


Shivam, Vineet, Arvind, Tanya and Vaishali
Shivam, Vineet, Arvind, Tanya and Vaishali

Here is a little author bio of each author of the Python and Machine Learning Training Course.

Shivam: Shivam is a Master's graduate currently working with TSInfo Technologies as a Senior Python Developer. He is expertise in multiple domains like Python, Django, and Databases like SQL Server, MySQL, etc.

Vineet: Vineet is working as a Senior Python developer with TSInfo Technologies. He has expert knowledge of Python Tkinter, Python Pandas, and databases like Oracle and SQL Server.

Arvind: Arvind is a Master's graduate working with TSInfo Technologies as a Senior Python Developer. He is proficient in using multiple Python libraries like NumPy, Tensorflow, and more.

Tanya: Tanya is a Postgraduate in computer applications and currently working with TSInfo Technologies as a Senior Python Developer. She is skilled in using various Python libraries like Matplotlib, Pandas, and Django framework.

Vaishali: Vaishali is a Master's graduate presently working with TSInfo Technologies as a Senior Python Developer. She is experienced in diverse Python libraries like Scikit learn, Turtle, and PyTorch.


Course Curriculum


  Module-1: Introduction to Machine Learning
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  Module-2: Introduction to Python Programming
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  Module-3: Basics of Python
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  Module-4: Exception handling in Python
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  Module-5: Working with Files in Python
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  Module-6: Object Oriented Programming in Python
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  Module-7: Python Multithreaded Programming
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  Module-8: Using Databases in Python
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  Module-9: Introduction to Tkinter Library
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  Module-10: Geometry Manager in Tkinter
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  Module-11: Widgets in Tkinter
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  Module-12: Tkinter with Object Oriented Programming
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  Module-13: Packaging and Distributing Executables
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  Module-14: Introduction to Python Turtle
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  Module-15: Using loops and conditional statement in Turtle
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  Module-16: Django introduction and installation
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  Module-17: Dynamic Web Pages in Django
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  Module-18: Template System in Django
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  Module-19: Models in Django
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  Module-20: Django Administration
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  Module-21: Forms in Django
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  Module-22: Generic, Advanced Views and URL configurations in Django
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  Module-23: Users and Registration
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  Module-25: Introduction to Pandas
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  Module-26: Basics of Pandas
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  Module-27: Operation in Pandas
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  Module-28: Project on Data Analysis using Python
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  Module-29: Introduction to Python NumPy
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  Module-30: Advanced Operations in NumPy
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  Module-31: Overview of Matplotlib
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  Module-32: Working with different type of plots in Matplotlib
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  Module-33: Statistical and Three-Dimensional Charts
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  Module-34: Plotting Data From DataSource
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  Module-35: Embedding Matplotlib in GUI (PyQt5, Tkinter, Django, wxFrame)
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  Module-36: Working with Seaborn Library
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  Module-37: Introduction to scikit learn
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  Module-38: Scikit learn supervised methods
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  Module-39: Scikit learn unsupervised methods
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  Module-40: Overview of PyTorch
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  Module-41: Linear Regression in PyTorch
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  Module-42: Preceptron in PyTorch
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  Module-43: Convolution & Deep Neural Network in PyTorch
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  Module-44: Image Recognition in PyTorch
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  Module-45: CIFAR10 Classification in PyTorch
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  Module-46: Overview of TensorFlow
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  Module-47: Convolutional and Recurrent Neural Networks
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  Module-48: Perception in TensorFlow
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  Module-49: TensorBoard Visualization
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Frequently Asked Questions


When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish. Once enrolled, the course will be lifetime access.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
Can I join the course as I am a Fresher?
Yes, you can join if you want to build your career in Python ana Machine Learning. We are covering enough course content, it will help you not only to get job easily but also will help you while working in Python. We will also take some live sessions on how to prepare for interviews and to doubt clears.
Do I get a course completion certificate?
Yes, you will get a course completion certificate and if you do not receive it, just send me an email at [email protected], We will send you the certificate.
Do I get an invoice so that I can get it reimbursed from my employer?
Yes. When you make the payment, you immediately get the invoice via email.