In a world where AI has become a driving force for the future of business and plays a significant role in our daily lives, having AI skills is like holding the key to endless opportunities. Therefore, starting a career in AI is a path that many aspire to take.
While entering the AI field may seem challenging, it’s definitely not impossible. Today, Sertis presents a roadmap for starting a career in AI within 10 months, providing a structured approach — from building essential foundational knowledge to creating real-world projects that will make your portfolio stand out and prepare you to compete in the job market.
Let’s embark on this exciting journey into a world of limitless opportunities together!
The AI career field offers diverse roles, including machine learning engineer, data scientist, and AI researcher. Although these roles share some common skills and can be developed by following this roadmap, choosing the one that aligns with your interests, and adjusting your roadmap accordingly will help you learn more effectively.
You can explore more about the different roles here: https://careers.sertiscorp.com/blogs
Months 1–2: Build a Strong Foundation
The first step is to build a solid foundation, covering essential subjects such as mathematics, algebra, probability, calculus, and statistics. You should also focus on programming (especially Python), data structures, and data manipulation.
Additionally, start learning about basic machine learning models, including supervised and unsupervised learning, as these topics are crucial for advancing in the AI field.
Months 3–4: Advance to Machine Learning and Deep Learning
Once you have a solid foundation, the next step is to dive deeper into the world of AI by studying different machine learning models, various algorithms, model validation, and hyperparameter tuning. During this phase, you’ll start seeing how AI can be applied in real-world scenarios and begin understanding how to use AI to solve problems.
You can also begin learning about neural networks and deep learning, which are cutting-edge AI models used across many applications. Try working on small projects like prediction models or data analysis tasks to enhance your skills.
Months 5–6: Focus on a Deeper Level of Specialization
After gaining a solid understanding of machine learning, it’s time to explore more advanced AI topics like natural language processing (NLP), computer vision, and reinforcement learning to find the areas that interest you the most.
During this period, it’s also a good idea to learn about machine learning Ops, which blends DevOps and machine learning, giving you an edge in the field.
Months 7–8: Work on Real-world Projects
Learning through hands-on experience is a crucial step. During this phase, start working on real projects, such as building sentiment analysis models, image classification, or creating a chatbot.
At the same time, learn how to deploy models on different cloud platforms like Google Cloud, AWS, or Microsoft Azure. Also, get familiar with frameworks like TensorFlow, PyTorch, and Keras.
Months 9–10: Ready to Enter the Job Market
By this stage, you should be ready to start working in the field. It’s time to create your portfolio and share your projects on GitHub, write technical blogs on platforms like Medium, and start preparing your resume for job applications.
Besides showcasing your technical knowledge, make sure to highlight a variety of projects that demonstrate your problem-solving skills and proficiency in using different tools.
Tips:
- Joining online communities like LinkedIn, Stack Overflow, Reddit, or Kaggle can help you connect with experts, exchange ideas, and pick up useful tips.
- After gaining knowledge in the later months, consider joining a hackathon or contributing to open-source projects to practice teamwork and managing larger projects.
However, always remember that learning and adapting are continuous processes. Within the AI field, different industries and companies have their own unique challenges. Therefore, it’s essential to stay open to new tools and innovations in the AI world, ensuring that your skills remain relevant and in demand.
Join us in this learning space as we grow together. Learn more about Sertis and the available job openings at: https://careers.sertiscorp.com/
