What You will learn in this program ?
30 Day Challenge - to become Zero to 🦸♂️🦸♀️ as Data Scientist
Introduction to Artificial Intelligence, Data Analytics & Road Map to become a Data Scientist
EXCEL
Data Preparation - Power Query & Tables
Data analytics- Formula & Pivot Table
Story Telling - Charts & Dashboard
PYTHON
Introduction to Python & Installing Python and its Libraries
Basic Python Programming for Data Analytics
STATISTICS & PROBABILITY
Introduction to Statistics & Use Case of Statistics on Data
Population and Sampling
BI tools - Tableu
Connect Tableau to a Variety of Datasets
Visualize Data in the Form of Various Charts, Plots, and Maps
BI tools - Power BI
Connect Tableau to a Variety of Datasets
Visualize Data in the Form of Various Charts, Plots, and Maps and Calculate Data NUMPY
Python Numpy functions
PANDAS
Day-14: Pandas for Data analytics in Python
MATPLOTLIB - Data Visualization
Matplotlib for data visualization
SEABORN- Data Visualization
Seaborn for data visualization
DATABASE - SQL
SQL basics for Data analytics
DATABASE - MONGODB
MongoDB basics for Data analytics
MACHINE LEARNING
Introduction to Machine Learning & its libraries
Supervised Learning - Classification
Salary Estimation using K-NEAREST NEIGHBOR
Supervised Learning - Regression
House Price Prediction using LINEAR REGRESSION
UnSupervised Learning - Clustering
Identifying the Pattern of the Customer spent using K-MEANS CLUSTERING
UnSupervised Learning - Association
Market Basket Analysis using APIRIORI
Reinforcement Learning
Web Ads. Click through Rate optimization using UPPER BOUND CONFIDENCE
Natural Language Processing
Sentimental Analysis using Natural Language Processing
DEEP LEARNING
Introduction to Deep Learning & its libraries
Multi-Layer Perceptron
Diabetes detection using Artificial Neural Network (MLP)
Convolutional Neural Network
Object Recognition using Pre Trained Model – Caffe
Brain Tumor Detection using CNN
Recurrent Neural Network
Stock Price prediction using LSTM
