This Course all in one. 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 provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered.

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

This Course will design to understand Data Visualization and Data Analysis with Machine Learning Algorithms with case Studies.

Data Analysis with Machine Learning Algorithms such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered.