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Chicago, Illinois
Machine Learning / AI
KASTRA Technologies – Machine Learning / AI Course Curriculum (Beginner → Expert)
About KASTRA Technologies
At KASTRA Technologies, we empower learners to become data-driven professionals ready for the modern analytics landscape. Our programs combine hands-on learning, real-world projects, and mentorship to prepare students for data-centric careers. Through structured training and innovative delivery, we transform beginners into confident analysts equipped to tackle business challenges using technology and insight.
Learn Machine Learning from Industry Experts with Real-Time Project Experience. Gain hands-on skills in data analysis, model building, and AI-driven problem-solving with practical exposure to real-world applications.
Enroll now for the Machine Learning & AI Course at Kastra Technologies
Why Choose Kastra Technologies
Kastra Technologies is one of the leading Machine Learning and AI training institutes in Chicago, offering 100% placement assistance.
Learn directly from industry professionals, gain hands-on experience through live projects, and build a strong foundation to launch a successful career in Machine Learning and Artificial Intelligence.
Kastra Technologies Course Content
Industry-focused curriculum delivered by real-time professionals with hands-on live projects.
Module 1 – Foundations of Machine Learning
Core Content
➤ ML basics, types (Supervised, Unsupervised)
➤ Datasets, features, labels
➤ Python setup (NumPy, Pandas)
Practical Task
Explore dataset (Iris/Titanic) using Pandas
Pro Tip
Focus on understanding data first
Learning Outcome
Strong ML fundamentals + Python workflow
➤ ML basics, types (Supervised, Unsupervised)
➤ Datasets, features, labels
➤ Python setup (NumPy, Pandas)
Practical Task
Explore dataset (Iris/Titanic) using Pandas
Pro Tip
Focus on understanding data first
Learning Outcome
Strong ML fundamentals + Python workflow
Module 2 – Data Cleaning & Feature Engineering
Missing values, encoding, scaling, feature creation.
Build clean dataset for training.
Build clean dataset for training.
Module 3 – Supervised Learning
Regression, classification, decision trees, KNN, bias vs variance.
Module 4 – Model Evaluation & Optimization
Metrics, cross-validation, GridSearchCV, overfitting vs underfitting.
Module 5 – Unsupervised Learning
K-Means, clustering, PCA, segmentation use cases.
Module 6 – Neural Networks & Deep Learning
Neural nets, TensorFlow, CNN basics, MNIST project.
Module 7 – End-to-End ML Project
Build full ML pipeline + deploy using Flask/Streamlit.