My name is Valentino Agazzi Mandozzi. I am a fourth-year Economics student at the Autonomous University of Barcelona. Over the past few years, I have developed a strong passion for Data Science, thanks to an incredible statistics professor I had in my second year. He introduced me to data analysis using R, and I instantly fell in love with it. My interest in the field grew so much that I embarked on a journey of self-learning, quickly grasping the basics of Data Analytics. Soon after, I decided to leverage the strong foundation in statistics and econometrics I had gained during my studies at UAB to redirect my professional career toward this area.
Choosing between Data Analytics and Data Science was not an easy task. In fact, even today, I have not made a definitive decision. Both fields share so much in common, and I am passionate about both. The process of uncovering insights hidden within data to improve decision-making for businesses, governments, or any other institution fascinates me. Additionally, I believe that developing and applying models for supervised, unsupervised, and deep learning to create AI algorithms that predict real-life events and automate various tasks is key to advancing technology and improving societal welfare.
For this reason, I couldn’t limit myself to just one area of study. Since both fields are closely related, I decided to gain extensive knowledge in both and become a professional Data Analyst and Data Scientist in the near future. To achieve this goal, I began dedicating my free time to deeply learning about Data Analytics and all the processes required to successfully transform data into actionable insights, such as data cleaning, exploratory data analysis (EDA), data preprocessing, data modeling, and communication. I took the first step in my learning journey by completing several courses on DataCamp, which I finished in July 2023. One year later, in June 2024, during my summer vacation, I began developing my portfolio with two projects, «Visualizing Climate Change» and «Effects of Different Public Expenditure Programs on Unemployment,» which are now publicly available on this website.
As I previously mentioned, the first step in this extensive learning process was successfully completed. I gained substantial knowledge from the courses, as well as strong experience and proficiency in SQL, Gretl, R, and particularly Excel and Python, along with many of the most popular libraries dedicated to Data Analysis, such as Pandas, NumPy, Matplotlib, Seaborn, Statsmodels, and more. However, I do not intend to stop here. My future plans include pursuing a Master’s Degree in Data Science after completing my current degree in Economics, and starting to work as soon as possible for companies that offer significant opportunities for ongoing learning, so I can continually improve my skills and competitiveness.
Beyond the technical aspects of Data Science, I also enjoy working in teams to manage large analytical projects. I believe that being surrounded by more experienced individuals with extensive work and life experiences is an incredible way to learn and grow both professionally and personally. Furthermore, meeting people from different places and cultures, with diverse backgrounds and perspectives, is an enriching experience.
If you would like to know more about me or simply have a conversation about any of these fascinating fields, please feel free to explore my portfolio and contact me via LinkedIn or email.
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Download my latest resume here!
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