Courses/Certifications

Built ML models with NumPy & scikit-learn, build & train supervised models for prediction & binary classification tasks (linear, logistic regression) and Built & trained a neural network with TensorFlow to perform multi-class classification, & build & use decision trees & tree ensemble methods

A deep understanding of mathematics that makes machine learning algorithms work and statistical techniques that empowered me to get more out of data analysis. It involves three sub courses (linear algebra, calculus, probability, and statistics)

Dived into the intricacies of visualizing and munging stock data, mastering techniques for informed decision-making. Delved into the world of random variables and distribution, gaining expertise in sampling and inference to enhance your analytical capabilities.

I have learned how to create, query, and configure databases and access and build system objects such as tables and performed basic database management including backing up and restoring databases as well as managing user roles and permissions.

Developed Python code for cleaning and preparing data for analysis - including handling missing values, formatting, normalizing, and binning data. Performed exploratory data analysis and apply analytical techniques to real-word datasets using libraries such as Pandas, Numpy and Scipy

Discovered the fundamental concepts and principles that underpin the inner workings of databases. Learned how to plan and execute a simple database development project, gaining hands-on experience in building and managing databases

This course define data science, its importance in todays data-driven world and the various paths that can lead to a career in data science.

Gained a comprehensive understanding of the workflow of machine learning projects, demystify AI terminology, and unravel the intricacies of data science project workflows.