1.Project 1 are completed successfully. 2. In this project are clear the concept of SQL. 3.In this project to understand the how to SQL work and how to write program in MYSQL workbench.  

1. The project-1 for Analyzing the Education trends in Tamilnadu are completed successfully. 2.This dashboard empowers mission driven organizations to harness the power of data visualization for social change. 3.Women are tracked away from science and mathematics throughout their education, limiting their training…

1. Project 2 Gender Bias in Science and Technical field completed. 2.Business RequirementsTitle: Literacy Rate in Tamilnadu. 3.In this project we use all concept of tableau.

1. Project 1 Completed. 2.Data Cleaning and Transformation using Pivot table and Charts for the Report on requirement of Team Hiring. 3.Company ABC Private Limited is manufacturing and selling below mentioned Products: Classic Cars,Motorcycles,Planes,Ships,Trains,Trucks and Buses,Vintage Cars. 4.In this project we use…

1. Project 1 Completed. 2. In project 1 we use all concept of Machine Learning. 3. Suppose you are appointed as a Data scientist in any Pharma Company. That company makes medicine for heart disease. Your senior manager has given several clinical parameters about a patient, can you predict whether or not the patient…

1. Project 2 completed. 2.Assume you are appointed as a Data scientist in any international humanitarian NGO, after the recent funding programmes, have been able to raise around $ 120 million. Now the CEO of the NGO call you to choose how to use this money strategically and effectively. The significant issues that comes…

1. Project 1 Completed. 2. In this project we use all concept of week 1 to week 10. 3. we finf its confidence interval. 4.Regression model.

1. Week 1 challeange completed. 2. In this week we learn AI & ML. 3. Basics of Probability. 4. Basic of Stastistiscs.  

1. Week 2 Challeange completed. 2. In this week we learn Basic of ML & AL. 3. Business moments. 4.Measure of Centeral tendency. 5.Measure of Disperssion. 6.Skewnees. 7.Kurtosis.

1. Week 3 Challeange completed. 2. In this week we learn Supervised learning predication. 3.  What is Linear Regression. 4. Difference between L1 & L2 Gradient descent method. 5. What are the different loss functions for regression. 6. What is the importance of learning rate.

1. Week 7 Challeange completed. 2. In this week we learn SVM. 3. Breif about Supported Vector Machine.  

1. Week 8 challenge completed. 2. In this week we learn k nearest neighbor. 3. Prons and crons.

1. Week 9 Challenge completed. 2. In thois week we learn K-mean. 3. Neural Network. 4. Deep learning.

1. Week 11 challenge completed. 2. In this week we learn Kmeans. 3. How to implement kmeans.

1. Project 1 completed. 2. In this project we use Basics of ML. 3. Python coding.

1. Project 2 completed. 2. In this project we use Clustering. 3. PCA.(Principle componet Analysis)        

1. Project 1 completed. 2. Project 1 - Implement and deploy CNN model in real-time using python on Fashion MNIST dataset. 3. In this project we use all concept of this course. 4. Using CNN models.

1. Project 1 completed in power bi. 2. In this project learn COVID-19 Vaccinations Trend Analysis.  

1. Project 2 - Supply and Demand Gap Analysis. 2. Aim : The aim of this project is to collect and analyze the data in detail of the Pickup point of the Airport and City Request id in Uber Request Data.