I’m going to change my career, from web dev to AI/ML engineer

Uvibirds.com
3 min readMar 20, 2024

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You know why I decided to change my career; these days I’m feeling awkward about my life. I’m working as a software engineer as a web dev but kind of feeling the salary getting low and my workforce also less productive and kind of think you know…It’s not too good to be in this way. Rapidly industry is changing with AI and ML tools. Most of the jobs are replaced not entirely but by some kind of. So am I supposed to live this way or change myself a bit more to align with the flow? So….I search search search….read many articles and watched many videos regarding the future of the software industry in 2024 and beyond. So I’m finding out my myself, you good to be changed, my dear.

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Transitioning from web development to AI/ML engineering is a significant but achievable career change. Here’s a step-by-step guide to help me make the transition. I’m going to follow this path and hope this helps you guys too.

  1. Learn the Basics of AI/ML: Start by familiarizing yourself with the fundamental concepts of artificial intelligence and machine learning. This includes understanding algorithms, data structures, linear algebra, statistics, and probability theory. Online resources such as courses, tutorials, and books can be valuable for self-paced learning.
  2. Master Python: Python is the primary programming language used in AI and ML development due to its simplicity, versatility, and extensive libraries for data manipulation, visualization, and machine learning. Make sure to become proficient in Python programming, including libraries like NumPy, Pandas, Matplotlib, and scikit-learn.
  3. Explore AI/ML Libraries and Frameworks: Dive into popular AI/ML libraries and frameworks such as TensorFlow, PyTorch, Keras, and scikit-learn. These tools provide pre-built modules and APIs for developing and deploying machine learning models efficiently.
  4. Understand Data Science Concepts: Gain a solid understanding of data science concepts, including data preprocessing, feature engineering, model selection, evaluation metrics, and model deployment. This knowledge is essential for working with real-world datasets and building predictive models.
  5. Take Online Courses and Certifications: Enroll in online courses and certification programs focused on AI and machine learning. Platforms like Coursera, Udacity, and edX offer comprehensive courses taught by industry experts and academics. Consider pursuing specialized tracks in areas such as deep learning, natural language processing, computer vision, or reinforcement learning.
  6. Work on Projects: Practice your skills by working on hands-on projects that involve solving real-world problems using AI and ML techniques. Start with small projects and gradually increase complexity as you gain confidence. Building a portfolio of projects will demonstrate your expertise to potential employers and collaborators.
  7. Join AI/ML Communities: Engage with AI/ML communities and forums to connect with fellow enthusiasts, share knowledge, and stay updated on the latest trends and developments in the field. Participate in online discussions, attend meetups, and contribute to open-source projects to expand your network and learn from others.
  8. Seek Internship or Entry-Level Positions: Look for internship opportunities or entry-level positions in AI/ML-related roles to gain practical experience and exposure to real-world projects. Even if the initial roles are not directly aligned with your career goals, they can provide valuable insights and networking opportunities within the industry.
  9. Continuously Learn and Adapt: The field of AI and machine learning is rapidly evolving, with new techniques, algorithms, and tools emerging regularly. Stay curious, keep learning, and be open to exploring new areas within AI/ML to stay relevant and competitive in your career.

By following these steps and investing time and effort into learning and practicing AI/ML skills, you can successfully transition from web development to a career as an AI/ML engineer. Remember that patience, persistence, and continuous learning are key to achieving your career goals. Let’s do it together. 😊

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Roadmap of my journey

I’m going to change my career, from web dev to AI/ML engineer

Becoming an AI engineer journey | Day 01

Becoming an AI engineer journey | Day 02

Becoming an AI engineer journey | Day 03

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