Data Science, Machine Learning , Artificial Intelligence, Graphical User Interface, Speech Recognition with Python

The course provides path to start career in Data Science , Artificial Intelligence, Machine Learning, Graphical User Interface and Speech Recognition

Problem Solving Approach

Impress interviewers by showing an understanding of the recent industrial trends

Learn Python Basic to Advance Concept with Numpy, Pandas, Matplotlib, Seaborn, Plotly Library

Scikit Learn Library in Depth

Machine Learning Algorithms such as Linear, Logistic, SVM, KNN, K Mean, Naïve Bayes, Decision Tree and Random Forest

Machine Learning Types Such as Supervise Learning, Unsupervised Learning, Reinforcement Learning

Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation

Case Study of Robotics (Unmanned Ground Vehicle)

Speech Recognition

Understand how you can create your own styles and use them in your applications

Learn wide variety of widgets, such as Button,Canvas ,Checkbutton, Entry, Label, Listbox, Menubutton, Message, Radiobutton, Scrollbar, Toplevel, Spinbox, PanedWindow, LabelFrame

Project on GUI and VUI such as Text to Speech, Digital Clock, Today's Day using Speech Recognition, Restart your Computer with Speech Recognition, Convert image to text and text to speech

It start with Basics

Only a passion for Learning

All software used in this course is either available for Free or as a Demo version

This course is intended for absolute bners in programming

it covered topics such as

1. Python Basic Concepts, Python Advance Concepts,

2. Numpy Library , Scipy Library , Pandas Library,

3. Matplotlib Library, Seaborn Library, Plotlypy Library.

4. The Machine Learning Algorithms such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered with case studies using Scikit Learn library.

5. Machine Learning Types such as Supervise Learning, Unsupervised Learning, Reinforcement Learning are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered.

6. Case Study on Artificial Intelligence (AI) for Unmanned Ground Vehicle (UGV)

7. CLI (Command Line Interface), GUI (Graphical User Interface) and VUI (Voice User Interface), Tkinter Library Use for GUI Development, Speech Recognition, Voice User Interface (VUI), Text to Speech, Speech to Text, Project of GUI and VUI

The course is ideal for bners, as it starts from the fundamentals and gradually builds up your skills in Machine Learning Algorithms, AI, Data Science, GUI, Speech Recognition, Python



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