Ensemble learning Bagging and Boosting

Introduction to Gray code. Binary to Gray code conversion & vise-versa

Data Preparation: Data Validation, Data Transformation, Data Reduction.

Classes of Models. Predictive, Pattern Recognition, Optimization, Project management, Risk Analysis.

Data Mining Definition and CRISP-DM

Introduction to SQL | Data types for MYSQL

Data Mining Analysis Methodologies. Supervised vs Unsupervised Learning.

Raspberry Pi versus Arduino.

Bitwise Operators in C. AND, OR, NOT, XOR, Left Shift and Right Shift operators.

Connecting to MySQL using PHP

Arduino, Developing on the Arduino.

Bellman's equation Reinforcement Learning-Part-II.

Raspberry Pi, Developing on the Raspberry Pi.

Data Preprocessing (Feature Selection and Merging)

Half Adders and Full Adders.

3D printing, Types of 3D Printing.

Looping statement in C | for Loop | Nested for loop.

Assignment Operators in C language.

Model Evaluation Metrics. F1score, ROC curve and AUC, Confusion Matrix.

Boolean Expressions Sum Of Product (SOP) Form.

Manufacturing PCB, Etching Board, Milling Board, Third Party Manufacturing, Assembly, Testing.

Windows (DOS)Commands

Model Evaluation Metrics. Accuracy, Precision and Recall.

Business intelligence: INTRODUCTION

Introduction to Computer Graphics.

Data Science comparison with BI, AI, ML and DW/DM

Arithmetic and Increment & Decrement Operators

Forms in HTML

Regular tessellations, Irregular tessellations.

What is Data Science | Applications of Data Science

Reinforcement Learning Introduction with Example.

API Introduction, Scraping, Clockodillo.

Rules of Boolean Algebra.

Why Closed? Why Open? Mixing Open and Closed Source.

The real world and representations of it.

BIG DATA Introduction