30 Days of Data Science Essentials

Welcome to "When Math Met Data"

Hello, and welcome to "When Math Met Data"! My name is Anastasia and I’m on a journey to dive deep into the world of data science and mathematics. As someone who has always been fascinated by numbers and the stories they tell, I’ve decided to start this blog to document my learning, share insights, and track progress. Through "When Math Met Data", I aim to build a solid foundation in data science fundamentals, enhance my skills, and hopefully inspire others who are beginning a similar journey.

This blog will be a collection of what I learn each day as I progress through a structured 30-day data science challenge. I’ll be spending around two hours daily, covering everything from foundational concepts in data science to more advanced applications like machine learning. Each week is designed to introduce a new topic in data science, offering a step-by-step learning path that builds up to practical skills and real-world applications.

Overview of My Learning Path

The challenge is structured across different weeks, with each week dedicated to a particular area of data science. Here’s a quick outline of the journey ahead:

Week 1: Data Science Fundamentals

This week is all about understanding the basics of data science. The first two days provide an overview of data science and how it’s applied in various fields, from healthcare to finance. Days 3 and 4 introduce Python as a programming language, setting up the tools and libraries I’ll need. By the end of the week, I’ll have worked with basic data types and structures, with a day to review and practice.

Week 2: Data Wrangling and Preprocessing

In Week 2, I’ll start handling raw data, which is an essential skill for any data scientist. Days 8 and 9 focus on cleaning data, dealing with missing values and outliers. Following that, I’ll learn about data transformations, feature engineering, and exploratory data analysis techniques, which help make sense of the data. Week 2 wraps up with a small EDA project to put these skills into action.

Week 3: Data Visualization

Visualization is key to communicating data insights, and this week, I’ll explore tools like Matplotlib and Seaborn. The week starts with basic charts, progressing to more complex visualizations that tell a story. By the end of Week 3, I’ll complete a visualization project that demonstrates my ability to create insightful charts and interpret data trends.

Week 4: Statistical Analysis and Hypothesis Testing

Week 4 dives into statistics, covering everything from descriptive statistics (mean, median, variance) to hypothesis testing. These skills are foundational for understanding data distributions, making predictions, and evaluating results. By the end of the week, I’ll have completed a mini-project to practice these statistical techniques.

Week 5: Introduction to Machine Learning

The final week of this challenge introduces machine learning. I’ll learn about the different types of machine learning models and build my first simple model, such as a linear regression model. This week provides a launching point for more advanced machine learning studies.

Looking Ahead: The Next Steps

If things go well, I plan to extend this learning journey with another 30-day challenge, covering more advanced topics like classification, clustering, model evaluation, and even some neural networks. Here’s a sneak peek:

Weeks 6-10

After mastering the basics, I’ll explore machine learning models, advanced feature engineering, deep learning, and model deployment. This path will allow me to build end-to-end projects, from data collection to model deployment, equipping me with the skills to tackle real-world problems.

Goals and Motivation

My goal with "When Math Met Data" is simple: to document my learning process in a structured way, share insights and challenges, and hopefully connect with others interested in data science. I’ll be posting summaries of what I learn each day, reflections on the process, and any tips that might help others who are just starting out.

"The computer was born to solve problems that did not exist before."
— Bill Gates

Over the next 30 days, I’ll be diving into the essentials—getting a handle on the basics so I can confidently move forward and tackle new, more complex challenges. I see this as more than just learning; it’s a stepping stone to uncovering, exploring, and solving new problems, ones I might not even know exist yet. Let’s keep pushing boundaries together, discovering new questions to answer along the way!

Thanks for joining me on this journey!