====== AI Course 1 ======
 

Topics for the three roles in AI.

AI Expert, AI Data Analyst, and AI Research Scientist.

1. AI Expert:

The AI Expert role focuses on providing a comprehensive understanding of artificial intelligence, including theoretical concepts, algorithms, and practical applications. It is for individuals interested in developing AI systems and solutions for real-world problems. The role includes the following topics:

- [[products:ict:ai:introduction_to_artificial_intelligence|Introduction to Artificial Intelligence: History, goals, and key concepts.]]

- [[products:ict:ai:machine_learning_intro|Machine Learning: Supervised, unsupervised, and reinforcement learning algorithms.
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- [[products:ict:ai:deep_learning|Deep Learning]]: Neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs).

- [[products:ict:ai:nlp|Natural Language Processing (NLP)]]: Understanding and processing human language.

- [[products:ict:ai:computer_vision|Computer Vision]]: Image and video analysis using AI techniques.

- [[products:ict:ai:ai_ethics|AI Ethics and Responsible AI]]: Ethical considerations in AI development and deployment.

- [[products:ict:ai:ai_tools_and_libraries|AI Tools and Libraries]]: Working with popular AI frameworks like TensorFlow and PyTorch.

- [[products:ict:ai:ai_applications|AI Applications]]: Implementing AI in various domains such as healthcare, finance, and robotics.

2. AI Data Analyst:

The AI Data Analyst part is tailored for individuals interested in working with data and using AI techniques to extract insights and make data-driven decisions. This part includes the following topics:

- [[products:ict:ai:data_analysis_fundamentals|Data Analysis Fundamentals]]: Data cleaning, exploration, and visualization.

- [[products:ict:ai:statistics_and_probability|Statistics and Probability]]: Key concepts for data analysis and machine learning.

- [[products:ict:ai:machine_learning_for_data_analysis|Machine Learning for Data Analysis]]: Applying supervised and unsupervised learning algorithms.

- [[products:ict:ai:data_preprocessing|Data Preprocessing and Feature Engineering]]: Preparing data for AI models.

- [[products:ict:ai:data_mining|Data Mining and Pattern Recognition]]: Identifying patterns and trends in data.

- [[products:ict:ai:big_data_and_cloud_computing|Big Data and Cloud Computing]]: Handling and analyzing large datasets using cloud-based tools.

- [[products:ict:ai:database_management|Database Management]]: SQL and NoSQL databases for data storage and retrieval.

- [[products:ict:ai:ai_in_business|AI in Business]]: Using AI to solve business problems and optimize processes.


3. AI Research Scientist:

The AI Research Scientist part is designed for individuals who want to pursue cutting-edge research in artificial intelligence and contribute to advancing the field. It covers the following topics:

- [[products:ict:ai:advanced_machine_learning|Advanced Machine Learning]]: Deep dive into advanced ML algorithms, optimization techniques, and model evaluation.

- [[products:ict:ai:reinforcement_learning|Reinforcement Learning]]: In-depth study of RL algorithms and their applications.

- [[products:ict:ai:probabilistic_graphical_models|Probabilistic Graphical Models]]: Learning and reasoning with probabilistic models.

- [[products:ict:ai:deep_reinforcement_learning|Deep Reinforcement Learning]]: Merging deep learning with RL for complex tasks.

- [[products:ict:ai:natural_language_processing_research|Natural Language Processing Research]]: Advanced NLP techniques, sentiment analysis, text generation.

- [[products:ict:ai:computer_vision_research|Computer Vision Research]]: Advanced topics in image and video analysis, object detection, and segmentation.

- [[products:ict:ai:ai_ethics_and_bias|AI Ethics and Bias]]: Addressing ethical challenges and biases in AI research.

- [[products:ict:ai:research_methodology|Research Methodology]]: Techniques for conducting AI research, writing research papers, and presenting findings.

- [[products:ict:ai:specialization_and_thesis|Specialization and Thesis]]: Focusing on a specific research area and completing an original research project.