There's no definitive "best" way to learn Data Science, as it depends on your learning style, background, goals, and available resources. Each approach has its pros and cons.
⛳ Online courses
➕ 𝘗𝘳𝘰𝘴: Flexible, often affordable, wide range of topics
➖ 𝘊𝘰𝘯𝘴: Lack of personalized feedback, requires self-discipline and knowledge what to learn
⛳ Bootcamps
➕ 𝘗𝘳𝘰𝘴: Intensive, structured learning, networking opportunities
➖ 𝘊𝘰𝘯𝘴: Can be expensive, fast-paced, may not cover topics in-depth, usually requires full time dedication and thus hard to combine with full time job.
By the way, in Germany more and more bootcamps are accredited by the government and one can get a voucher to study there from "Agentur für Arbeit". However not every bootcamp cares what will happen with you after the finishing of the intensive study program there. So it's a good idea to check which kind of support during the job search they offer for graduates before you enroll.
⛳ Individual mentor
➕ 𝘗𝘳𝘰𝘴: Personalized guidance, tailored to your needs and schedule, industry insights
➖ Cons: Good mentors are expensive, the outcome highly dependent on mentor quality
A combination of these approaches often works well.
For instance:
✅ Start with online courses to grasp fundamentals
✅ Join a bootcamp for hands-on experience and networking
✅ Find a mentor for ongoing guidance and career advice
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