I love Mathematics which was the one reason that made me study engineering. I went through it with much interest and enthusiasm till I got my MSc degree in Structural Engineering! Surprisingly, this was the end of one story and the start of a completely different one.Studying engineering improved my hidden skills of analytical thinking and problem-solving. But till this moment, I found nothing that fulfilled my potential of using these skills at their ultimate levels except coding! During my thesis work, I dealt with a lot of coding stuff and Machine Learning, which were more interesting to me than my field of study. I found that I love to automate every task! So, I decided to start a new journey to master Artificial Intelligence. I know it is going to be a long journey, but no problem at all, it is a journey to my passion. This is me as I tend to learn new things every while, I even started playing Tennis at the age of 28!During this journey, I learned three different topics: Programming, Data Science, and the Theory of Machine Learning. I started by reading a book on programming with Python, which gave me fundamentals in scripting and Data Structures. Thanks to Data Analysis Nandodegree from Udacity, I learned a lot about Pandas and NumPy libraries to properly deal with large datasets and generate descriptive statistics and visualizations using the matplotlib library. Since then I have decided to take the Statistics and Data Science MicroMasters provided by MIT starting with the course, "Machine Learning with Python-From Linear Models to Deep Learning". Actually, it was a magnificent beginning! As I learned a lot about support vector machines, neural networks, unsupervised learning, and most importantly reinforcement learning. During the rest of my MicroMasters courses, I have deepened the basic concepts of probability and learned lots of fundamental tools of Statistics in the following two courses. The ending course was "Data Analysis: Statistical Modeling and Computation in Applications" which is a wonderful blend between theory and applications in different areas like Network Analysis, Time Series, and Gaussian Processes.To connect everything together, I have started my PhD in Structural Engineering focusing on applying machine learning models to control structures subjected to seismic events. I am willing to apply these models in different fields too. So, Stay Tuned!