Frequently Asked Questions
Everything you need to know about our AI programming courses, enrollment process, and career support services.
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Ask Us DirectlyWhat makes NeuralPath different from other AI bootcamps?
NeuralPath focuses exclusively on practical neural network development with real industry projects. Unlike traditional bootcamps that cover broad topics superficially, we dive deep into AI/ML with hands-on experience building production systems. Our instructors are active practitioners at companies like Google, Tesla, and OpenAI, ensuring you learn current industry practices.
How intensive are the programs really?
Our programs are designed for serious career transformation. Expect to dedicate 40-60 hours per week including lectures, labs, project work, and assignments. The intensity is comparable to a tech company's engineering bootcamp. We provide this upfront so students can plan accordingly and maximize their learning outcomes.
What is your job placement success rate?
89% of our graduates secure AI/ML positions within 6 months of graduation. This includes roles at major tech companies, startups, and traditional companies building AI capabilities. Our career services team works individually with each student from week 1 through job placement.
What programming languages will I learn?
Python is our primary language, as it's the industry standard for AI/ML development. You'll master Python for data science, TensorFlow, PyTorch, and deployment frameworks. We also cover SQL for data management and basic knowledge of cloud platforms (AWS, GCP) for model deployment.
What kind of projects will I build?
You'll build production-quality AI applications including: computer vision systems for medical imaging, natural language processing chatbots, recommendation engines, fraud detection systems, and autonomous decision-making algorithms. All projects are portfolio-ready and demonstrate real-world problem-solving skills to employers.
What are the prerequisites for enrollment?
For our Foundations program: basic programming experience (any language) and high school mathematics. For Deep Learning Mastery: solid Python knowledge and some exposure to machine learning concepts. For Innovation Lab: previous ML experience or completion of our Deep Learning program.
What career support do you provide?
Comprehensive career services including: resume and portfolio optimization, mock technical interviews, salary negotiation coaching, direct connections to hiring partners, alumni networking events, and ongoing job search support.
What hardware do I need?
Minimum: laptop with 8GB RAM, recent processor, and stable internet. Recommended: 16GB+ RAM, dedicated graphics card (GTX 1060 or better). However, we provide cloud-based GPU instances for all heavy computational work, so any modern laptop will suffice.