Can you become an Applied Scientist without a degree?

An alternative career path to becoming an Applied Scientist with its major challenges, possible benefits, and some ways to hack your way into it.

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It is possible to become an Applied Scientist without a formal degree, but it can be challenging. Most employers in the field of Applied Science, especially in industries like AI/ML and Data Science, typically require a bachelor's degree or higher in a related field such as computer science, mathematics, or statistics. However, there are alternative paths you can take to achieve this career goal.

Achieving a Career as an Applied Scientist without a Degree

1. Build a Strong Foundation: Start by gaining a solid understanding of the fundamentals of computer science, mathematics, and statistics. You can do this through self-study using online resources, textbooks, and tutorials. Focus on topics such as algorithms, data structures, probability, and linear algebra.

2. Develop Practical Skills: Gain hands-on experience by working on real-world projects. Build a portfolio showcasing your work and highlight the skills you have developed. Participate in open-source projects, contribute to online communities, or collaborate with others on data-related projects.

3. Online Courses and Bootcamps: Take advantage of online courses and bootcamps that offer comprehensive training in AI/ML and Data Science. Platforms like Coursera, edX, and Udacity offer a wide range of courses taught by industry experts. Completing these courses and earning certificates can help demonstrate your knowledge and commitment to potential employers.

4. Networking and Mentorship: Attend industry conferences, meetups, and networking events to connect with professionals in the field. Seek out mentors who can provide guidance and support as you navigate your career path. Building a strong professional network can open doors to job opportunities and provide valuable insights.

5. Showcase Your Skills: Create a strong online presence by sharing your work, insights, and expertise. Contribute to relevant blogs, forums, or social media platforms. Participate in Kaggle competitions or other data science challenges to demonstrate your skills and problem-solving abilities.

Hacks and Advice

• Open-source Contributions: Contribute to open-source projects related to AI/ML and Data Science. This not only helps you gain practical experience but also allows you to collaborate with experienced professionals and showcase your skills.

• Internships and Freelancing: Look for internships or freelance opportunities to gain practical experience and build your network. Many companies offer internships to individuals with strong technical skills, even without a formal degree.

• Continuous Learning: Stay updated with the latest advancements in AI/ML and Data Science. Read research papers, follow industry blogs, and participate in online communities. Continuous learning is essential to stay competitive in this rapidly evolving field.

Potential Difficulties, Benefits, and Differences

Not having a formal degree may present some challenges in the job market. Many employers use a degree as a screening criterion, and some roles may have strict educational requirements. Additionally, without a degree, you may face competition from candidates who possess formal education.

However, there are benefits to pursuing a career as an Applied Scientist without a degree. The field of AI/ML and Data Science values practical skills and experience, and if you can demonstrate your abilities through a strong portfolio and relevant projects, you can still be considered for job opportunities.

Compared to a conventional academic path, the alternative route may offer a more practical and hands-on learning experience. It allows you to focus on building specific skills and gaining real-world experience, which can be attractive to employers. However, it may require more self-motivation, discipline, and dedication to continuously learn and stay updated in the field.

In summary, while it is possible to become an Applied Scientist without a degree, it requires a strong foundation in computer science, mathematics, and statistics, practical experience through projects and internships, continuous learning, networking, and showcasing your skills. It is important to be aware of the potential challenges and benefits associated with this alternative path.