With product and project management experience in IT, looking forward to developing innovative solutions in the Artificial Intelligence: GEN AI, ML fields.

Blog posts

2025

Methodologies for product or service

less than 1 minute read

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Difeerent methodologies could be applied depending on area and problem type. Each of it serves best when selected correctly.

Overview and key aspects of the product management

less than 1 minute read

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Product management is complex, as it covers different areas of knowledge and skills. To master it takes time and practice. With the overview you can step into the shoes of the product manager role and practically do some exercises in order to understand and get insights into product/service creation and development.

Unveiling the Dimensions of Product Differentiation Strategies

2 minute read

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In a crowded market, product differentiation is the key to standing out and winning customer loyalty. However, differentiation is not a single-point solution; it operates across multiple vectors, each representing a continuum of opportunities.

2024

AI and Human Learning: A Double-Edged Sword

5 minute read

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Artificial Intelligence (AI) has come a long way in mimicking the human learning process. From its ability to observe, imitate, and store information to analyzing vast amounts of data and finding intricate patterns, AI has reached impressive heights. With human-designed models, AI can reflect and adapt in ways that are undeniably sophisticated. However, despite these advances, there are fundamental differences between AI’s capabilities and the richness of human experience, learning, and adaptability.

Exploring the Google Cloud Advanced Generative AI for Developers Learning Path

6 minute read

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The Google Cloud: Advanced: Generative AI for Developers Learning Path has been an incredibly enriching experience, offering not only in-depth theoretical knowledge but also hands-on, practical labs that allowed me to gain invaluable skills. From mastering foundational concepts like Attention Mechanism and Transformer Models to applying cutting-edge technologies in Vertex AI Studio and MLOps, this learning path provided the perfect blend of theory and practice. Below, I’ll walk you through the key topics I explored and how the practical labs played a crucial role in solidifying my understanding.

Why Create a GitHub Website?

3 minute read

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Creating a website on GitHub serves multiple purposes:

  1. Showcasing Projects: It provides a platform to display the projects I’ve worked on, demonstrating my skills and knowledge to potential employers or collaborators.
  2. Documenting My Journey: A website is a great way to document my learning experiences, insights, and the challenges I’ve faced. It allows me to reflect on my progress over time.
  3. Building a Portfolio: Having a personal website is essential in the tech industry. It helps establish an online presence, which can be beneficial for networking and career opportunities.
  4. Learning Git: Creating the website was a practical way to become familiar with Git, tools I would need for collaborative work in the future.

How to Get Practical Experience Without a Coding Background

2 minute read

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Even though you don’t have Python experience, the good news is that it’s never too late to start, and you don’t have to jump into hardcore coding from day one. Here’s what I’d recommend if you’re interested in bridging the gap between theory and application without getting overwhelmed by coding:

My Journey Through MIT 6.0001: Completing the Theory Part and Tackling Assignments

4 minute read

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Having embarked on the journey of MIT 6.0001 (Introduction to Computer Science and Programming in Python), I found myself immersed in the world of programming and computer science. Completing the theory part of the course has been a fulfilling experience, offering me invaluable insights into problem-solving and algorithmic thinking. As I transition to the assignments, I want to share my experience, the challenges I faced, and the exciting path that lies ahead.

Tackling the Theory Part of MIT 6.036 Introduction to Machine Learning with No Python Coding Experience: A Personal Journey

4 minute read

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Taking MIT 6.036 (Introduction to Machine Learning) was an eye-opening and transformative experience. Coming from a non-coding background, I decided to focus primarily on the theory part of the course, and what I walked away with has given me a strong understanding of machine learning at a conceptual level. Here’s a recap of my experience, the challenges I faced, and what I learned along the way.