IBM Machine Learning Professional Certificate

Machine Learning, Time Series & Survival Analysis. Develop working skills in the main areas of Machine Learning: Supervised Learning, Unsupervised Learning, Deep Learning, and Reinforcement Learning. Also gain practice in specialized topics such as Time Series Analysis and Survival Analysis.

Sr. No	Course	Status
01.	Exploratory Data Analysis for Machine Learning	✅
02.	Supervised Machine Learning: Regression	✅
03.	Supervised Machine Learning: Classification	✅
04.	Unsupervised Machine Learning	✅
05.	Deep Learning and Reinforcement Learning	✅
06.	Specialized Models: Time Series and Survival Analysis	✅
07.	IBM Machine Learning Professional Certificate Specialization

About this Professional Certificate

This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Machine Learning and leverage the main types of Machine Learning: Unsupervised Learning, Supervised Learning, Deep Learning, and Reinforcement Learning. It also complements your learning with special topics, including Time Series Analysis and Survival Analysis.

In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Machine Learning.

Projects

Exploratory Data Analysis for Machine Learning

The challenge is to help the company analyze all relevant customer data to develop focused customer retention programs based on the telco customer churn dataset.

Supervised Learning: Regression

I used regression models to predict house sale prices based on the information regarding the demography (income, population, house occupancy) in the districts, the location of the districts (latitude, longitude), and general information regarding the house in the districts (number of rooms, number of bedrooms, age of the house).

Supervised Learning: Classification

The goal of this project is to create Classification models that will predict which class the flower is, based on petal and sepal sizes and the models are going to be evaluated based on their Predictability.

Unsupervised Learning

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Deep Learning and Reinforcement Learning

Customer churn is the percentage of customers that stopped using your company's product or service during a certain time frame. The objective is to figure out why a customer leaves and when they leave with reasonable accuracy, it would immensely help the organization to strategize their retention initiatives manifold.

Specialized Models: Time Series and Survival Analysis

The main objective of the project is to build a time series model that will be able to forecast the climate for the next 12 months. We will be using the LSTM method to find the most accurate model.