Full Stack Artificial Intelligence with Python
The Full Stack Artificial Intelligence with Python course is a comprehensive program designed to equip learners with cutting-edge AI skills, covering machine learning, deep learning, natural language processing, and AI model deployment. This course provides hands-on experience with real-world projects, ensuring learners gain practical expertise in AI development. With a strong emphasis on Python, participants will master AI frameworks, data science libraries, and model optimization techniques. The curriculum follows a structured approach, starting from fundamental programming concepts to advanced AI applications, including cloud-based AI and API integration. Whether you are a beginner or a professional looking to upskill, this course will prepare you for a career in AI and data science.
Course Features
- 40 instructor-led classes covering full-stack AI concepts
- Hands-on experience with industry projects and real-world AI applications
- Access to recorded lectures and study materials for revision
- Practical coding exercises, assignments, and quizzes for concept reinforcement
- Industry-standard AI frameworks, tools, and cloud-based deployment training
- One-on-one mentorship and career guidance
- Industry placement/ in house job placement after course completion
Software You Will Learn
- Python, NumPy, Pandas, Matplotlib, Seaborn
- Scikit-Learn, TensorFlow, Keras, PyTorch
- Flask, FastAPI, Docker, Kubernetes
- AWS, Azure, Google Cloud, Hugging Face
Ideal For
- Students and graduates looking to enter the AI industry
- Software engineers and developers transitioning into AI roles
- Data analysts and business intelligence professionals
- Entrepreneurs and business leaders interested in AI-driven solutions
- Researchers and academicians exploring AI advancements
Career Opportunity
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- Deep Learning Engineer
- NLP Engineer
- AI Consultant
- Computer Vision Engineer
- AI Research Scientist
Course Module
Python for AI & Data Science
- Python Basics: Syntax, Variables, Data Types, and Control Structures
- Object-Oriented Programming in Python
- Working with NumPy and Pandas for Data Manipulation
- Data Visualization with Matplotlib and Seaborn
- Exploratory Data Analysis (EDA) and Feature Engineering
Machine Learning Foundations
- Introduction to Machine Learning and AI
- Supervised Learning: Regression and Classification Models
- Model Evaluation Techniques and Performance Metrics
- Unsupervised Learning: Clustering and Dimensionality Reduction
- Feature Selection and Hyperparameter Tuning
Deep Learning with TensorFlow & PyTorch
- Introduction to Deep Learning and Neural Networks
- Building Neural Networks with TensorFlow and Keras
- Convolutional Neural Networks (CNNs) for Image Processing
- Recurrent Neural Networks (RNNs) and Sequence Modeling
- Transformer Models and Attention Mechanisms
Natural Language Processing (NLP)
- Fundamentals of NLP and Text Processing
- Tokenization, Stemming, Lemmatization, and Word Embeddings
- Sentiment Analysis and Named Entity Recognition (NER)
- Building Chatbots and Conversational AI Models
- 20. Large Language Models (LLMs) like GPT and BERT
AI Model Deployment & Cloud Integration
- Flask and FastAPI for AI Model Deployment
- Docker and Kubernetes for Containerized AI Models
- Deploying AI Models on AWS, Azure, and Google Cloud
- Model Optimization and Scaling AI Solutions
- API Integration and AI as a Service
Advanced AI Topics
- Reinforcement Learning and Game AI
- Explainable AI (XAI) and Model Interpretability
- Generative AI and GANs (Generative Adversarial Networks)
- Ethical AI, Bias in AI, and AI Governance
- AI for IoT and Edge Computing
AI Project Development & Case Studies
- AI in Healthcare: Medical Image Analysis
- AI in Finance: Fraud Detection and Risk Prediction
- AI in Retail: Demand Forecasting and Personalization
- AI in Autonomous Systems: Self-Driving Cars and Robotics
- AI for Cybersecurity and Threat Detection
Capstone Project & Career Preparation
- End-to-End AI Project Development
- Resume Building and AI Career Guidance
- Interview Preparation for AI and Data Science Jobs
- Building a Portfolio on GitHub and Kaggle
- Final Capstone Project Presentation
Course Study Plan
- Week 1 - 4: Python Programming and Data Science Fundamentals
- Week 5 - 8: Machine Learning & AI Foundations
- Week 9 - 12: Deep Learning and Neural Networks
- Week 13 - 16: NLP and AI Model Deployment
- Week 17 - 20: Advanced AI Topics and Case Studies
- Week 21 - 24: Capstone Project and Career Readiness
Projects
- 5+ Real-World AI Projects based on different industries like healthcare, finance, and automation
- 10+ Mini AI Projects including predictive analytics, NLP-based applications, and image processing
Materials
- 100+ Hours of Recorded Sessions for Self-Paced Learning
Course FAQ
Do I need prior programming experience?
No, this course starts from the basics of Python and progresses to advanced AI concepts.
Will I receive a certificate upon completion?
Yes, a professional certificate from Brilliant Brains Valley will be awarded
Can I access recorded classes if I miss a session?
Yes, all sessions are recorded and available for later access.
Will I work on live AI projects?
Yes, the course includes 5+ real-world AI projects to build your portfolio.
What support is provided after course completion?
We offer career support, interview preparation, and mentorship to help you secure AI jobs.
৳ 400.00
৳ 200.00
- Students: 0
- Lessons: 40
- Durations: 6
- Category: Technical Learning
