Q: What about me?

I am a full-time IT infrastructure professional with extensive experience in enterprise & cloud architecture and operations. As technology evolves rapidly, I realized that artificial intelligence is the core driving force of the future. Stepping out of my comfort zone, I decided to dive into the field of AI, exploring how to implement AI technologies in real-world scenarios to drive innovation for businesses and individuals. This website serves as a platform for documenting my growth, sharing knowledge, and connecting with learners like you.

• Exploring Cutting-Edge Technologies: Understanding the latest advancements in AI, machine learning, and related fields.
• Career Transformation Insights: Sharing my experience transitioning from IT infrastructure to AI and product management.
• Resource Sharing: Curating learning materials, course recommendations, and useful tools.
• Case Studies: Discussing how AI transforms enterprise management and product design through practical projects.

Q: What motivates me to work in and with AI technology?

My motivation to work in and with AI technology stems from their potential to revolutionize various aspects of our lives. It has the potential to solve complex problems or improve everyday experiences; living simply and enjoying life is my desire.

Q: What are the crucial technical skills in the AI field?

AI field invloves computing infrastructure, data, machine learning and software engineering, there are key skills that crucial for the success.

• Require proficiency in programming languages, Python is a common denominator due to its widespread use in data processing, machine learning, and software development. Other languages like Jave, Scala, and SQL are also valuable across these roles.
• Understand basic data structures like arrays, lists, stacks, queues, trees, graphs and algorithms like sorting, searching, optimization.
• Familiarity with version control systems, especially Git.
• Knowledge of databases and data storage mechanisms is important, this includes understanding how to store, retrieve, and manipulate data efficiently.
• Basic understanding in machine learning, as ML integration into various applications is becoming more common. Principles of software development, such as object-oriented programming, functional programming, and software design patterns, are applicable across.
• Familiarity with DevOps practices and automation tools is beneficial. This includes continuous integration and continuous deployment, containerization technologies like Docker, and orchestration tools like Kubernetes.
• Knolwedge of cloud services (AWS, Azure, GCP) is increasingly important as many data, ML and software applications are hosted on cloud platforms.

Q: How should you start if you share the same interests?

Don't overthink, start small. Learning the basics of AI and machine learning, online courses, university degrees, or specialized training programs can provide this domain knowledge. Apply your knowledge by working on projects; this could be as simple as a personal project or contributions to open-source projects. It is a rapidly evolving field, following news, research, and reading books. Remember, the journey into anything is a marathon, not a sprint; it requires dedication and a passion for continuous improvement. Keep going and stay relevant.

Q: How to not lose the momentum?

Don't stop grinding; the momentum and desire need to be enforced and pushed out from ourselves sometimes or most of the time.

Q: Are you affiliate or sponsored?

Disclaimer: I am not affiliated with, sponsored by, or endorsed by any of the training publishers, or authors of the products and books featured on my website. All are included and reviewed based on my personal interests and skill development progression. Any brand names, logos, or trademarks featured or referred to on my website are the property of their respective trademark holders.