FAQs

Ethical Use of AI Tools: Bias and Fairness, Privacy and Security. Best Practices: Effective Tool Usage, AI Project Management.

Google Cloud AI: Introduction, Using AI Services, Deploying AI Solutions. AWS AI Services: Introduction, AI and Machine Learning Services, Hands-On Projects. Azure AI: Introduction, AI and Machine Learning Services, Deploying AI Solutions.

Google AutoML: Introduction, Automated Model Building, Evaluation and Deployment. H2O.ai: Introduction, AutoML Features, Hands-On Projects.

Matplotlib and Seaborn: Introduction, Creating Plots and Charts, Customizing Visualizations. Plotly: Introduction, Interactive Visualizations, Hands-On Projects. Tableau: Introduction, Creating Dashboards, Data Integration and Analysis.

OpenCV: Introduction, Basic Image Processing, Advanced Computer Vision. TensorFlow and PyTorch for Computer Vision: Image Classification and Segmentation, Transfer Learning, Hands-On Projects.

NLTK (Natural Language Toolkit): Introduction, Text Processing and Analysis, Building NLP Pipelines. spaCy: Introduction, Advanced NLP Tasks, Hands-On Projects. Transformers (Hugging Face): Introduction, Pre-trained Models, Custom NLP Applications.

Deep Learning Frameworks: Comparison of Frameworks, Selecting the Right Framework. Keras for Deep Learning: Sequential and Functional API, Training and Tuning Models. OpenAI Gym: Introduction, Reinforcement Learning Environments, Hands-On Projects.

Scikit-Learn: Introduction, Basic Features and Functions, Hands-On Projects. TensorFlow and Keras: Introduction, Building Neural Networks, Advanced Features. PyTorch: Introduction, Building and Training Models, Advanced Applications.

Overview of AI Tools: Categories of AI Tools, Criteria for Selecting AI Tools. Setting Up Your Development Environment: Required Software and Hardware, Working with IDEs and Notebooks.