- Python LLM: Should have very strong in-depth knowledge in Python Programming
- Programming Fundamentals: Proficiency in programming languages commonly used in AI, such as Python, FastAPI.
- AI/ML Libraries: Familiarity with basic libraries and tools like scikit-learn, Pandas, and NumPy.
- API Usage: Know-how to integrate pre-trained AI models via APIs, e.g., cloud-based AI services.
- Data Management: Skills in collecting, preprocessing, and handling datasets.
- AI Concepts: Familiarity with concepts like machine learning, supervised and unsupervised learning, and foundational algorithms.
- Deep Learning Frameworks: Familiarity with frameworks like TensorFlow, PyTorch, or Keras.
- Custom Model Training: Ability to fine-tune and train models on specific datasets, understand overfitting, and apply regularization techniques.
- Integration Skills: Proficiency in integrating AI functionalities into applications, web services, or mobile apps.
- Optimization: Knowledge of optimizing model performance and reducing latency for real-time applications.
- Version Control and Collaboration Tools: Proficiency with tools like Git, which are essential for collaborative development.
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