Artificial Intelligence

Artificial Intelligence (AI) Course at iGAP Technologies

Our Artificial Intelligence (AI) Course is designed to equip students with the skills and knowledge required to excel in the field of AI. Through a well-structured curriculum covering Python programming, SQL, statistics, machine learning, deep learning, NLP, large language models (LLMs), OpenCV, and AI model deployment, students will develop a strong foundation in artificial intelligence and its applications.

With a focus on practical learning, including hands-on coding, real-world projects, programming assessments, and mock interviews, students will gain the expertise needed to build AI-powered systems, automate tasks, and analyze complex datasets.

Course Breakdown by Subject:

Python for AI:

✅ Learn Python fundamentals, including data structures, loops, functions, and object-oriented programming.
✅ Work with AI-specific libraries such as NumPy, Pandas, Matplotlib, Seaborn, TensorFlow, and PyTorch.

SQL for Data Management:

✅ Understand Structured Query Language (SQL) for efficient data retrieval and management.
✅ Learn how to clean, transform, and analyze large datasets for AI applications.

Statistics & Mathematics for AI:

✅ Master probability, hypothesis testing, linear algebra, and calculus, essential for AI and ML models.
✅ Learn about gradient descent, optimization techniques, and loss functions.

Machine Learning:

✅ Gain expertise in supervised and unsupervised learning.
✅ Work with ML algorithms like Linear Regression, Decision Trees, KNN, SVM, and Clustering.
✅ Learn model evaluation techniques and hyperparameter tuning.

Deep Learning & Neural Networks:

✅ Understand the workings of Artificial Neural Networks (ANNs), CNNs, and RNNs.
✅ Train deep learning models using TensorFlow and PyTorch.
✅ Explore Generative AI and Transformer models.

Natural Language Processing (NLP) & LLMs:

✅ Learn about text preprocessing techniques like tokenization, stemming, and lemmatization.
✅ Work with NLP models such as TF-IDF, Word2Vec, and Transformer models (BERT, GPT, Llama).
✅ Build chatbots and AI-powered text analysis systems.

Computer Vision with OpenCV:

✅ Learn image processing, object detection, and facial recognition using OpenCV.
✅ Apply CNNs for image classification and deep learning for real-time vision tasks.

AI Model Deployment & MLOps:

✅ Deploy AI models using Flask, FastAPI, and Streamlit.
✅ Learn MLOps concepts to automate AI workflows.
✅ Integrate models with cloud platforms like AWS, Google Cloud, and Azure.

Version Control & Agile Methodology:

✅ Use Git & GitHub for collaboration and version control.
✅ Understand Agile development processes, including Scrum and Kanban.

Assessments & Industry Readiness:

✅ Take objective tests, programming tests, and hands-on assignments to reinforce learning.
✅ Participate in mock interviews to enhance job readiness and problem-solving skills.
✅ Work on real-world AI projects to build a strong portfolio.

By covering these topics in-depth, our AI Course prepares students for roles such as AI Engineer, Machine Learning Engineer, Data Scientist, and Computer Vision Engineer. Join us and take the first step toward mastering Artificial Intelligence and shaping the future! ????