About Machine Learning
This elective equips you with hands-on skills to preprocess data, train models, understand algorithms, and evaluate results.
You will explore supervised vs unsupervised learning and work with real-world datasets to create predictive and intelligent systems.
Skills Gained: Data preprocessing, model training, algorithms, supervised vs unsupervised learning, model evaluation.
Role Mapping: Machine Learning Intern, Data Science Trainee, ML Model Tester.
Learner Benefit: Opportunity to work on predictive models and data projects, even remotely via cloud-based tools.
Learning Modules
Data Preprocessing
Cleaning, transforming, and preparing raw data for model training to ensure accurate and reliable results.
Model Training
Building machine learning models, training algorithms, and tuning parameters to optimize performance and predictions.
Algorithms & Techniques
Understanding supervised vs unsupervised learning, regression, classification, clustering, and recommendation algorithms.
Model Evaluation
Measuring model accuracy, precision, recall, F1 score, and other evaluation metrics to ensure reliability of predictions.
Practical Projects & Cloud Tools
Apply machine learning on real-world datasets and predictive projects, even remotely via cloud-based platforms and tools.
Career Path
Machine Learning Intern
Assist in data preprocessing, model building, and training supervised and unsupervised models. Gain hands-on experience with ML pipelines and predictive analytics.
Data Science Trainee
Analyze datasets, identify patterns, build predictive models, and learn statistical and machine learning techniques for actionable insights.
ML Model Tester
Evaluate ML models for accuracy and performance, test algorithm outputs, and validate model predictions for deployment readiness.
AI/ML Developer
Design and deploy ML models into applications, implement algorithms, and optimize systems for intelligent decision-making processes.
Predictive Analytics Specialist
Develop predictive models using historical data, simulate business scenarios, and provide insights to improve operational and strategic decision-making.
Data Engineer
Prepare and manage large datasets, build data pipelines, and support ML teams with clean, structured data for model development.
AI Research Assistant
Work on experimental ML/AI models, explore novel algorithms, and support research projects aimed at improving AI solutions.
Business Intelligence Analyst
Translate data insights from ML models into actionable business recommendations, dashboards, and reports for stakeholders.
Awards and Recognitions








