Data Science & Analytics 

Python Introduction

Applications of python

Python Variable types

Python Anaconda navigator download

Day 1 Data Science - Python For Data Science

Python Tuples

Tuples and dictionaries

Python Classes and Objects

Python class and inheritance

Day 2 Advanced Python Programming

Pandas Introduction

Pandas Datastructures

Pandas series input

Pandas Dictonary

Day 3 Pandas Library – Introduction

Day 3

Pandas access series elements

Pandas Data frames

Pandas Data frames- II

Day 4 Pandas Library – Data Structures vvvvvvv

Day 4

Mathematical Functions

Numpy Introduction

Numpy Arrays

Numpy Shapes & Attributes

Day 4

Numpy Slicing - I

Numpy - Simple Plot

Numpy Slicing - II

Numpy Floor Function

Day 6 Numpy – Sort, Search, and Counting Functions

I/O With Numpy

Matplotlib - Introduction

Matplotlib PyLab

Day 7 Matplotlib, Histogram Using Matplotlib IO With Numpy

Types Of Plots

MATPLOTLIB - Figure Function

MATPLOTLIB - II

MATPLOTLIB- SUBPLOT

Day 8 Matplotlib Library – Introduction, Pyplot API Types Of Plots

Seaborne Introduction

Seaborne - Joint Plot

Seaborne- Joint Plot & Sub plot

Day 9 Seaborn  Library

Sci Kit Introduction - I

Sci Kit - Learn Example

Scikit Learn - Example - II

Day 10 SKLearn Library

Google Co Lab - Introduction

Google Co Lab - II

Google Co Lab - Graphical Output

Day 11 Google Colab Notebook

Date & Time Introduction - I

Date & Time Introduction - II

Date & Time Introduction Arithmetic

Day 12 Python – Date and Time, Data Wrangling

Data Wrangling Introduction

Data - Grouping & Wrangling

Data - Concat

Reading html

Day 13 Python – Data Aggregation

Stemming_and_lemmatization

Sentence Tokenization

Day 14 Python – Word Tokenization, Stemming, and Lemmatization

Data Visualization Introduction

Data Visualization - Simple Plot

Day 15 Python – Data Visualization

Statistical_analysis

Mean , Median & Mode

Statistical_analysis_II

Day 16  Python – Statistical Analysis

Types of distribution-I

Types of distribution-II

Poisson Distribution\

Day 17 Python – Types Of Distribution

Correlation

Chi Square Test

Correlation - III

Day 18 Python – Correlation, Chi-Square Test , Linear Regression

Tableau - I

Tableau Installation

Tableau - Visual Analysis

Day 19 Tableau – Introduction and Tools

Analysing_different_data_sources

Combining fields & dashboards

Day 20 Data Sources , Worksheets

Power BI - Introduction

Power BI - Architecture

Power BI - Data Source

Day 22 Power-BI – Introduction, Installation Steps, and Architecture

Power BI - Dashboard

Power BI - Data Visuvalisation

Day 23 Power-BI – Data Modelling, Visualization Options Excel Integration

Spatial data science Introduction

Covid Disease Prediction-I

Covid Disease Prediction-II

Day 21 Spatial Data Science For Covid-19 Disease Prediction

Ensemble Learning - I

Ensemble Techniques - II

Parkinson's Disease

Day 24 Parkinson’s Disease Prediction – XG Boost Classifier

Random Forest Regression- I

House Price Prediction- I

House price Prediction - II

Day 25 House Price Prediction using Random Forest Regression

K Means Clustering - I

K Means Segmentation

Customer Segmentation Implementation - I

Day 26 Customer Segmentation Using ML – K-Means Clustering

Decision Tree Algorithm

Home Loan Prediction Implementation

Day 27 Home Loan Prediction using Decision Tree Classifier

NLP Introduction

NLP techniques - II

Spam Classification Implementation

Day 28 Spam Classification using NLP

CNN Introduction - I

Types of CNN - II

CNN Implementation - I

Day 29 Hand-Written Digit Recognition Using CNN

ANN Introduction - I

Deep Learning Concepts

Churn Prediction Implementation

Day 30 Churn Prediction using Deep Learning