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# Mastering Programming for Free: A Path to Success Without a Degree

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Chapter 1: My Journey into Programming

Hello! I’m Axel, a psychologist, data analyst, and PhD candidate in Computational Neuroscience. Learning programming has opened numerous doors for me, both in the professional realm and in academia. When I applied for research internships, my programming abilities set me apart from other candidates. Recently, these skills helped me secure my first data analyst position at Disney, and my understanding of data science even earned me a scholarship for a PhD in Germany.

In this article, I aim to share how you, too, can learn programming for free using various resources and tips.

Section 1.1: The Motivation Behind Learning Programming

You might wonder why I decided to learn programming. My fascination with Neuroscience began in my second semester, where I observed that lab members possessed a basic understanding of programming. They were engaged in data analysis and some were even exploring machine learning with EEG data. A friend and colleague advised me that instead of getting lost in extensive readings about the brain, mastering programming would be the smartest move for my neuroscience aspirations. At the time, I didn’t grasp the importance of his words, but it became clear to me a year later.

Programming opened a world of possibilities, and I quickly realized that my Python skills were highly valued in every lab I approached.

Subsection 1.1.1: Choosing Python as My First Language

Based on recommendations, I chose to learn Python as my initial programming language. In 2019, Python was gaining popularity for its simplicity and robust libraries. It allowed me to design psychological experiments using Psychopy, conduct data analyses with Pandas, and create visualizations with Seaborn and Matplotlib. However, starting out was quite challenging due to my lack of a computer science background and my limited computer skills, compounded by not having a computer at all.

Python programming language on a computer screen

Section 1.2: Finding Help on Coursera

After working as a housekeeper in the USA, I finally saved enough money to purchase a computer. In 2020, I discovered the incredible platform Coursera, which offered a wealth of free resources for learning. I was overjoyed to find that I could access programming courses from prestigious universities and companies at no cost.

Determined, I created a roadmap to master data science. I began with the Python Crash Course from Google, followed by Python for Everybody from the University of Michigan to deepen my understanding. After grasping the basics, I enrolled in Google’s Data Analytics Professional Certificate, which I still consider the best introductory course for data analysis. Within three months, I progressed from zero knowledge to a solid understanding of Python and data analysis tools like Excel, SQL, and Tableau.

Chapter 2: Advancing in Data Science

The first video titled "How I Learned to Code in 4 MONTHS & Got a Job Offer (no CS Degree)" showcases the journey of learning programming and securing job opportunities without a formal degree.

However, as I tackled data analysis projects, I truly honed my programming skills. My next goal was to dive into data science.

Section 2.1: Embracing Mathematics in Learning

Surprisingly, I entered college without a solid grasp of calculus, having only taken an introductory statistics course. Yet, I continued my education on Coursera, where I enrolled in the Machine Learning Specialization by Andrew Ng from DeepLearning.AI and Stanford University. This course demystified the mathematical concepts behind machine learning for me, including derivatives, which I had never encountered before. Understanding the math was critical for grasping how artificial intelligence functions.

I followed this with the Deep Learning Specialization to further explore the mathematics behind neural networks.

Section 2.2: Essential Tips for Aspiring Programmers

If you're considering starting your programming journey, my first piece of advice is to clarify your motivation. Are you interested in data analysis, data science, AI, web development, or something else? Identifying your goal is crucial.

Next, develop a structured approach to mastering programming. I have written several articles on setting up an ultralearning project to help you excel in any subject.

Additionally, practical experience is vital. Simply watching tutorials won’t suffice; you need to engage in coding your own projects. Watching a complete Python course on platforms like freeCodeCamp made me feel knowledgeable, but I struggled to implement what I learned independently.

Lastly, be patient. Mastery takes time, just like learning a new language. With consistent effort, you will reach your goals, I assure you.

Learning programming was a challenging endeavor for me. With no prior computer science or mathematics background, I had to navigate this journey on my own. Thankfully, the plethora of free resources available made a significant difference. Ultimately, it was the hands-on experience of coding my own projects that distinguished me from my peers.

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