Topics to be covered in Data Science 30 days free webinar:
Day 1 - Python for Data Science (5 Solved end-to-end Data Science Projects in Python)
Day 2 - Advanced Python
Day 3 - Pandas Library - Introduction
Day 4 - Pandas – Data Structures
Day 5 - Numpy library - Array Operations | Mathematical Functions
Day 6 - Numpy - Sort , Search and Counting Functions
Day 7 - Matplotlib , Histogram Using Matplotlib | I/O With Numpy
Day 8 - Matplotlib Library - Introduction , Pyplot API | Types Of Plots
Day 9 - Seaborn Library
Day 10 - SKLearn Library
Day 11 - Google Colab Notebook
Day 12 - Python – Date and Time , Data Wrangling
Day 13 - Python – Data Aggregation
Day 14 - Python – Word Tokenization , Stemming and Lammetization
Day 15 - Python – Data Visualization
Day 16 - Python – Statistical Analysis
Day 17 - Python – Types Of Distribution
Day 18 - Python – Correlation ,Chi-Square Test , Linear Regression
Day 19 - Tableau – Introduction and Tools
Day 20 - Tableau – Data Sources , Worksheets
Day 21 - Spatial DataScience For Covid-19 Disease Prediction
Day 22 - PowerBI – Introduction,Installation Steps|Architecture.
Day 23 - PowerBI – Data Modelling , Visualization Options|Excel Integration.
Day 24 - Parkinson’s Disease Prediction - XGBoost Classifier
Day 25 - House Price Prediction - Random Forest Regression
Day 26 - Customer Segmentation Using ML - K-Means Clustering
Day 27 - Home Loan Prediction - Decision Tree Classifier
Day 28 - Spam Classification - NLP
Day 29 - Hand Written Digit Recognition Using Python - CNN
Day 30 - Churn Prediction - Deep Learning
Day 2 - Advanced Python
Day 3 - Pandas Library - Introduction
Day 4 - Pandas – Data Structures
Day 5 - Numpy library - Array Operations | Mathematical Functions
Day 6 - Numpy - Sort , Search and Counting Functions
Day 7 - Matplotlib , Histogram Using Matplotlib | I/O With Numpy
Day 8 - Matplotlib Library - Introduction , Pyplot API | Types Of Plots
Day 9 - Seaborn Library
Day 10 - SKLearn Library
Day 11 - Google Colab Notebook
Day 12 - Python – Date and Time , Data Wrangling
Day 13 - Python – Data Aggregation
Day 14 - Python – Word Tokenization , Stemming and Lammetization
Day 15 - Python – Data Visualization
Day 16 - Python – Statistical Analysis
Day 17 - Python – Types Of Distribution
Day 18 - Python – Correlation ,Chi-Square Test , Linear Regression
Day 19 - Tableau – Introduction and Tools
Day 20 - Tableau – Data Sources , Worksheets
Day 21 - Spatial DataScience For Covid-19 Disease Prediction
Day 22 - PowerBI – Introduction,Installation Steps|Architecture.
Day 23 - PowerBI – Data Modelling , Visualization Options|Excel Integration.
Day 24 - Parkinson’s Disease Prediction - XGBoost Classifier
Day 25 - House Price Prediction - Random Forest Regression
Day 26 - Customer Segmentation Using ML - K-Means Clustering
Day 27 - Home Loan Prediction - Decision Tree Classifier
Day 28 - Spam Classification - NLP
Day 29 - Hand Written Digit Recognition Using Python - CNN
Day 30 - Churn Prediction - Deep Learning
