How to land an AI internship without experience?

Artificial Intelligence (AI) is revolutionizing entire industries, and companies are in a quest for talents capable of mastering these technologies. But how can you enter this rapidly expanding field if you lack experience? A work-study program in AI might just be the perfect solution! This model blends theoretical training with professional immersion, offering a gateway to future-proof careers. In this article, discover why a work-study program is a strategic choice, how to secure a contract despite being a junior profile, and all the tips to maximize your chances of success.

Why choose a work-study program in AI?

Opting for a work-study program in artificial intelligence provides a unique professional springboard. Firstly, this format enables you to gain valuable hands-on experience, which employers often require, while pursuing a degree. Moreover, the employability of work-study participants is high: according to France Travail, 7 out of 10 apprentices secure a job within 7 months of completing their contract. Additionally, work-study programs facilitate networking, a crucial asset in a sector where collaborations between startups, large corporations, and research labs are common. Furthermore, the AI market is thriving: according to Statista (2025), the sector is predicted to experience continuous growth between 2025 and 2031 in France with a total increase of 18.4 billion euros. The demand for technical skills (machine learning, data science) and soft skills (project management, AI ethics) is enormous. A work-study program in this field ensures positioning in a promising sector with long-term opportunities.

What types of work-study programs are available in AI?

The field of artificial intelligence offers a wide variety of work-study pathways, tailored to different profiles and aspirations. Whether you’re interested in algorithmic research, model deployment, or innovative applications like natural language processing, there’s a work-study program for you. Here are the main possible specializations: Here’s the updated table without the column on targeted careers, while maintaining a clear and optimized structure:

Type of AI Work-Study	Main Missions	Relevant Sectors
Machine Learning	– Design of classification, regression, clustering models– Development of predictive models	Finance, healthcare, e-commerce
MLOps / AI Engineering	– Deployment and maintenance of AI models- Optimization of data pipelines– Monitoring & scalability	Industry, tech, cloud services
Generative AI / NLP	– Development of generative models (text, image, voice)- Creation of chatbots, semantic analysis	Marketing, education, communication, virtual assistants

What career paths are available?

A work-study program in artificial intelligence opens doors to highly sought-after careers with excellent growth prospects. Here’s what awaits you after graduation. Depending on your specialization and level of education, you can aim for positions such as:

• Data Analyst: Data analysis and visualization (SQL, Tableau/PowerBI).
• Data Scientist: Design of predictive models (Python, Machine Learning).
• Machine Learning Engineer: Deployment of AI models in production (MLOps, Docker).
• AI Engineer: Development of chatbots or language processing tools (GPT, Transformers).
• AI Consultant: Assisting companies in their AI transformation.

What profile is needed to join a work-study program in AI?

Securing a work-study program in artificial intelligence is accessible to various profiles, from Bac +2 in reconversion to specialized Bac +5. But what skills are truly essential? Here are the key criteria companies look for.

Essential Technical Skills

To apply for a work-study program in AI, certain technical foundations are often required:

• Python: The king language of AI (libraries like NumPy, Pandas, Scikit-learn).
• SQL: For manipulating and querying databases.
• Machine Learning: Understanding algorithms (regression, neural networks).
• Data science tools: Jupyter Notebook, Git, TensorFlow/PyTorch (a plus).
• Math/Stats: Linear algebra, probabilities, optimization (level varies by position).

Tip: Even without professional experience, a portfolio (GitHub projects, Kaggle competitions) can make a difference.

Soft skills sought by employers

AI is a rapidly evolving field where human qualities matter as much as technical skills. Curiosity is essential to stay updated with innovations through technology watch. An AI model is built methodically (testing, documentation), requiring a rigorous attitude and problem-solving skills to translate business needs into technical solutions. Given that tools are constantly changing, it’s necessary to adapt to these shifts (e.g., transition from traditional ML to Generative AI).

Education Level: Bac+2, Bac+5, or career change?

A Bac+2 (BTS, DUT) is possible for technical roles (assistant data scientist, AI technician), especially with an engineering school. The most common profile ranges from Bac+3 to Bac+5 (Professional License MIASHS, Master AI, engineering schools). Recruiters favor these programs for strategic positions. As for career changes, this is possible through boot camps or university programs tailored to this path.

What training should you pursue?

Artificial intelligence is a complex and multidisciplinary field, so several types of training can lead to a work-study program depending on your level of education and career goals. 

• After high school: Some degrees in computer science or applied mathematics offer a progressive specialization in AI, sometimes with a work-study option starting in L3.
• Bac +2 to Bac +3: Programs like the BUT computer science or professional licenses oriented towards data provide a solid foundation in programming, statistics, and algorithmics, paving the way for an AI work-study program.
• Bac +5: Masters in artificial intelligence, data science, or computer engineering increasingly incorporate work-study courses, focusing on applied research and industrial projects.

The training offered by Liora is designed to meet the current needs of the AI market. Our programs combine academic rigor, practical experience on real projects, simulations, and professional support towards employment or work-study.

How to find your work-study in AI?

Artificial intelligence is attracting more and more students, which makes competition significant for finding a work-study program. Here are the essential levers to activate to maximize your chances of securing a contract.

Where to apply?

Work-study opportunities in AI can be found on major platforms like LinkedIn, JobTeaser, or Welcome to the Jungle. Set up alerts and target tech companies, AI startups, or innovation labs. Networking can also play a decisive role: attend events, webinars, or connect with alumni from your training already in the field. Spontaneous applications, often overlooked, can also open doors. Directly contact the AI teams of certain companies by emphasizing your motivation and potential.

Polishing your resume and cover letter

A good AI-ready resume doesn’t just list skills: it tells a story. Highlight your personal or academic projects related to data, even modest ones. A simple data analysis, a predictive model, or a chatbot developed as part of a school project can catch attention. Don’t forget to add a link to your GitHub or online portfolio. The cover letter must be clear and sincere. Explain why you’re interested in artificial intelligence, what you hope to learn, and how you can contribute to the company. A good letter links your education, ambitions, and the organization’s needs.

Switching to AI: Testimonial from one of our learners

Sarah Lemarcis decided to give a new direction to her career by enrolling in one of our AI programs, Machine Learning Engineer, in work-study. Coming from another field, she embarked with determination into the tech universe, establishing her place in a still largely male sector. “I turned my career around by joining Liora. I chose the work-study format because, to me, learning is practice. Without practice, you don’t really learn.” Convinced that one learns better by doing, Sarah chose the work-study route to test her knowledge against real-world challenges. An inspiring testimonial for those considering a career change to artificial intelligence.

Conclusion

A work-study program in artificial intelligence represents a concrete opportunity to enhance skills while immersing oneself in a future-proof sector. Whether you’re a student, changing careers, or simply curious about the data world, suitable training exists, companies are hiring, and projects abound. Discover our courses