What will you Learn in the Project?
1. Learn many concepts and business scenarios of Data science domain
2. Understand data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing
3. How to do Data Loading and EDA?
4. How to do Data Processing?
This unique course contains 10 Demos and 2 Industry standard project with self-paced solution explainer
The demos and projects will cover following:
Data Loading and EDA
Prediction with ensemble method Random Forest regressor
Validation and preparing the final result
- Data Loading and EDA: Load each the data sample present and check the data contains in train and test. Perform the exploratory data analysis to check the insight of the data.
- Data Processing Check all the data and find any missing value in any columns. Also check for any multiple categorical variables in it. Also check whether we can use any column that can be removed or not.
- Prediction with ensemble method Random Forest regressor. Tune the parameter of the given model if there are any performance enhancements and data split and predict the result on the model with train data.
- Validation and preparing the final result. Finally validate the data for the accuracy observer based upon the test data we got
This course does NOT cover the theory part so it assumes that you know the theory of Data Science.
This course covers followings:
* Demos :
Pandas and Numpy
SQL and Reporting tool
Model Deployment and Tools
-Taxi Trajectory and Predicting Final Destination
– Detect the online bidding fraud by bots
Who this course is for?
1. College Freshers
2. Anyone who wants to see what are the use cases where Data science applies and how to implement various concepts
3. Any one who wants to start their journey in Artificial Intelligence