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AI Developer Career Accelerator
The AI Developer Career Accelerator is a comprehensive training program designed to take learners from foundational AI concepts to hands-on experience with real-world projects and internships. This program integrates content from Foundations for AI and AI Developer Career Accelerator, ensuring a structured learning path for aspiring AI professionals.
Free
✅ Earn Recognized Certifications at No Cost
✅ Practical Skill Development through Experience
✅ Explore New and Emerging Career Paths
✅ Real-World Experience Through Internships
Explore courses covered in this career tracks’
This is structured a progressive learning path covering Fundamentals & Advanced AI development to create a career-oriented, hands-on curriculum with strong industry alignment, projects, mentorship, and job-ready skills.
AI Developer Fundamentals – Prerequisite Course (Track 1)
Master Python, Math & Machine Learning in 12-Weeks
AI Developer Advanced Course-Hands-On, Project-Based Learning-(Track 2)
24 week long hands-on training program with interships and certifications.
Goal: Build a strong foundation in programming, math, and AI concepts before transitioning to hands-on development.
Practical Skill Development through Experience
📌 Hands-On Project:
Build a machine learning-powered recommendation system to analyze user preferences (Pandas, Scikit-learn).
Explore New and Emerging Career Paths
📌 Module 1: Python for AI Development
🔹 Introduction to Python (variables, loops, functions)
🔹 Object-Oriented Programming (classes, inheritance, modularization)
🔹 Data structures & algorithms (linked lists, recursion, sorting)
Track 1: AI Developer Fundamentals (Prerequisite Course)
Duration: ~12–16 weeks
Focus Areas: Python, Data Science, Machine Learning Basics, AI Ethics
📌 Module 1: Python for AI Development
🔹 Object-Oriented Programming (classes, inheritance, modularization)
🔹 Data structures & algorithms (linked lists, recursion, sorting)
📌 Module 2: Mathematics for AI
🔹 Probability & Statistics (distributions, Bayes theorem, hypothesis testing)
🔹 Calculus (gradients, derivatives, optimization for ML models)
📌 Module 3: Data Science & Machine Learning Fundamentals
🔹 Supervised vs. Unsupervised learning basics
🔹 Feature engineering & evaluation metrics (accuracy, precision, recall)
📌 Module 4: AI Ethics & Responsible AI Development
🔹 Privacy & security concerns
🔹 Regulatory guidelines & ethical AI decision-making
Track 2: AI Developer Advanced Course (Hands-On, Project-Based Learning)
Goal: Transition from theory to real-world AI applications, covering deep learning, automation, cloud deployment, DevOps for AI.
Duration: ~16–24 weeks
Focus Areas: Deep Learning, NLP, AI Ops, Model Deployment
📌 Hands-On Project:
Build & deploy a real-time fraud detection system using deep learning, optimized for cloud scalability (TensorFlow, Kubernetes).
📌 Module 1: Advanced Machine Learning & Deep Learning
🔹 Convolutional & recurrent neural networks (CNNs, RNNs, LSTMs)
🔹 Reinforcement learning & model optimization
📌 Module 2: Natural Language Processing (NLP)
🔹 Sentiment analysis, chatbots, speech recognition
🔹 Fine-tuning pretrained AI models (BERT, GPT)
📌 Module 3: AI Deployment & Cloud Integration
🔹 Supervised vs. Unsupervised learning basics
🔹 Feature engineering & evaluation metrics (accuracy, precision, recall)
📌 Module 4: AI Ethics & Responsible AI Development
🔹 Monitoring model performance & retraining strategies
🔹 Automating ML pipelines with Apache Airflow
Additional Features
✅ Community Support & Peer Collaboration – Study groups, mentor-led discussions, internship networking opportunities.
✅ Industry-Level Tutorials & Code Challenges – Interactive coding exercises, algorithm optimization challenges.
✅ Career Services – Resume guidance, mock interviews, open-source project contributions.
✅ Capstone AI Development Project – Solve a real-world AI problem and present findings.