Data Journey
My journey
2022
- August(08/08)
- Learning the basics of SQL and Python on Mimo.
- Choosing which university will provide me with the best job opportunities so I can start working as soon as possible.
- Career plan presentation on Prezi and discussing it with family.
- Solving problems on Brilliant, there’s a data science course.
- Starting the IBM Data Science course on Coursera- €38.99 per month - week 22/08 to 28/08
- Starting to better understand the importance of business mindset and storytelling to be a better professional.
- Starting to learn SQL and resuming Python learning on the Mimo app.
- September:
- Handling the basics of Jupyter Notebook
- Doing some exercises on Mimo.
- October:
- Starting a degree in Data Science and Artificial Intelligence with two subjects: Programming Fundamentals and Professional Skills.
- In terms of professional skills, I learned more about storytelling by making presentations.
- I do some base conversions in Programming Fundamentals and start studying Python again.
- On the Datacamp platform, I start a basic Python course.
- On Coursera, I’m doing Data Science Methodology.
- November:
- I’ve been studying the third block on Coursera, data science methodology.
- A bit of Python basics on Datacamp.
- I’ve been able to validate professional skills and programming fundamentals, so I don’t have any subjects enrolled this semester.
- December:
- End the DataCamp Python Basics course
- Start an intermediate Python course
- Finish DataCamp free access €300 to continue, maybe next semester.
- Try to find some dream job in a big company to adapt the skills and be prepared for the interview.
- Continue intermediate Python course
2023
- January:
- Finish the intermediate Python course on DataCamp.
- Finish the Python Project or Data Science on Coursera
- Start Databases and SQL for Data Science with Python on Coursera
- February:
- Finish Databases and SQL for Data Science with Python on Coursera
- Start the Semester in the UAX
- Start Data Analysis with Python on Coursera
- March:
- Still in the Data Analysis with Python Course
- Making some exercises with SQL databases for the University, connecting some tables, and making conclusions
- April:
- Finish the Data Analysis with the Python Course
- Start the Data Visualization Course
- May:
- Continue with the Data Visualization Course
- Studying for university exams
- June:
- Take 4 exams and pass 2
- July:
- Finish all the exams and pass 3 of 4
- Failed Numeric Methods, because the exams were too hard for me
- August
- Finish Data Visualization Course
- Start Machine Learning
- September
- Pause the Coursera course
- Start Kaggle machine learning course
- Start an experience course - week of a data scientist (not finished)
- October
- Start the classes at the university
- Continuing the intermediate Python in Datacamp
- Trying to understand how a project is made
- November
- Start a project with DataCamp about marketing with python
- Stop the DataCamp project, have to pay the fee
- Did some exercises in SQL, Python, and Spark
- Start doing scrapping with BeautifulSoup
- December
- Did some projects with web scraping
- Start learning about Docker
- Start to visualize some work that I can do for companies.
2024
- January
- Drop out of college
- Try to find some project to do by myself
- Start working on a coworking space project
- February:
- Continue to work on the coworking project
- Change all the projects to work in my new Ubuntu
- March:
- Start to get more knowledge in statistics and probability at work.
- Getting more familiar with connecting databases with visualization tools.
- April:
- Continue to work with data visualization in the Cowroking project.
- May:
- Start work with PowrBi in Windows with the Coworking project.
- Start Nodd3r course.
- June:
- Making python exercices in the Nodd3r course.
- Making SQL exercices in the Nodd3r course.
- July
- Continue to do some SQL exercises
- August
- Continue to do some SQL exercises
- Septemeber
- Finish the SQL module
- Start the MongoDB module
- October
- Made a Streamlite app for the FilmAffinity project and made a LinkedIn post
- Finish MongoDB module
- Made a LinkedIn post about Sentiment Analysis with TextBlob library
- Start Numpy module
- November
- Continue with the Numpy module
- December
- Finish the Numpy Module
- Made some adjustments and improvements to the coworking space project
- Start the Pandas module
2025
- January
- Finish The Pandas module
- Start with the Machine Learning module
- Fabruary
- Finish The Machine Learning module
- Use the Coworking Project as final project and implementing machine learning into this project
- Start to callaborate with a ONG (Generar-ECO)
- March
Strengths (Internal, Positive) | Weaknesses (Internal, Negative) |
---|---|
Technical Skills (Python, SQL, MongoDB, PowerBI, ML) | Falta de experiencia en empresas |
Experiencia con datos reales (Películas, Coworking) | Necesidad de mejorar los proyectos |
Mentalidad Autodidacta | Sin títulos en educación formal |
Capacidad de Adaptación |
Opportunities (External, Positive) | Threats (External, Negative) |
---|---|
Crecimiento del sector de Data Science | Competencia en el mercado |
Proyectos personales como Carta de Presentación | Requisitos estrictos en algunas ofertas |
Interés en I.A |
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