Description

Python (Internals, do’s and don’ts) Architecture, Data Structure

Installation of Anaconda Prompt

Jupyter Notebook – An Overview

Shortcut Keys in Jupyter Notebook

Data Types in Python

 

Python, Reading & Writing Files in Python

Rules for Naming the Variables

List, Tuple, Set, Dictionary

Introduction to Files and Directories

Introduction to the Command Prompt or Terminal Paths

Text Files – Reading from a Text File Opening a File using with

Loops and Conditionals in Python

If, Elif and Else Condition

For and While Loop

 

Data Analysis, Manipulation with NumPy

Machine Learning Libraries

NumPy – Hands On

 

Pandas Python Data-Science Package to Manipulate, Calculate and Analyze Data

Pandas – Hands On

 

Exploratory Data Visualization in Python with Matplotlib

Learn How to Explore, Visualize and Extract Insights from Data

Data Visualization

Matplotlib – Hands On

Seaborn – Hands On

 

Statistical Thinking in Python (Part 1) Build the Foundation

You Need to Think Statistically and Speak the Language of Your Data

Measures of Central Tendency

Measures of Dispersion

IQR Statistics – Hands On

 

Supervised Learning & Un-Supervised Learning

Classification, Regression, Fine-Tuning Your Model

Supervised Learning

Unsupervised Learning

Linear Regression

Metrics in Linear Regression – Hands On in Linear Regression

 

Logistic Regression

Logistic Regression

Metrics in Logistic Regression

Hands On in Logistic Regression

 

Linear Regression

Linear Regression

Metrics for Linear Regression

 

Pre-Processing for Machine Learning in Python

Introduction to Data Preprocessing

Standardizing Data

Exploratory Data Analysis

Missing Values

Outliers

Standardization, Normalization, Feature Scaling and Selection

 

Tree-Based Models Classification and Regression Trees

Decision Tree

Bagging

Boosting Random Forest

 

Fundamentals of Neural Network

Neural Network

 

Project

Use Data-Science Packages, Analysis, Visualization, Create Model, Extract Pure Data etc