Feature Engineering Courses and Certifications

Coursera

Advanced Data Science Techniques (with AWS Integration)

Master sophisticated ML models and AWS deployment through hands-on projects covering feature engineering, time series analysis, and cloud-based machine learning pipelines.

• Coursera
• 1 day 5 hours 29 minutes
• Self-Paced
• Paid Course

AI For Data Analysts

Discover how to build AI-powered data agents without coding experience. Master automated data collection, ML model training, and ethical AI deployment across industries like retail and healthcare.

• Coursera
• 10 hours 40 minutes
• Self-Paced
• Paid Course

AWS Certified Machine Learning - Specialty

Master the complete machine learning lifecycle on AWS, from data engineering to model deployment, preparing you for the specialty certification exam.

• Coursera
• 7 hours 28 minutes
• Self-Paced
• Paid Course

Coursera

Databricks Machine Learning Fundamentals

Master production-grade machine learning on Databricks with hands-on experience in data preparation, MLflow tracking, and model deployment for real-world applications.

• Coursera
• 3 hours 53 minutes
• Self-Paced
• Paid Course

Coursera

Production AI Model Development and Ethics

Master production ML lifecycle from feature engineering to ethical deployment, covering PyTorch optimization, model evaluation, and responsible AI documentation practices.

• Coursera
• 10 hours 5 minutes
• Self-Paced
• Paid Course

Board Infinity

Apply AI & Machine Learning to Financial Forecasting

Master AI and machine learning techniques to transform financial data into accurate forecasts using Python, regression models, and time series analysis for strategic decision-making.

• Coursera
• 20 hours 11 minutes
• Self-Paced
• Paid Course

Packt

Machine Learning Foundations

Master feature engineering, core ML algorithms, and advanced techniques like neural networks and reinforcement learning through hands-on Python implementation.

• Coursera
• 7 hours 22 minutes
• Self-Paced
• Paid Course

Packt Credential

AI Engineer Associate

Master essential AI engineering skills through feature engineering, deep learning frameworks, and AI agent development for real-world applications.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

EDUCBA

Python: Apply & Evaluate Sales Forecasting with Time Series

Master advanced time series techniques in Python to build, evaluate, and compare SARIMA and Prophet models for accurate sales forecasting and data-driven decision making.

• Coursera
• 5 hours 12 minutes
• Self-Paced
• Paid Course

Coursera

AI Data: Analyze, Govern, Plan

Master AI data pipeline diagnostics, governance standards, and workflow planning through real-world scenarios including GDPR compliance and bottleneck resolution.

• Coursera
• 2 hours 13 minutes
• Self-Paced
• Paid Course

Packt

Databricks ML in Action

Master practical machine learning on Databricks platform with hands-on projects covering MLflow, Vector Search, AutoML, and complete ML lifecycle from data ingestion to deployment.

• Coursera
• 13 hours 23 minutes
• Self-Paced
• Paid Course

Packt

Building, Evaluating, and Operationalizing ML Models

Master the complete ML lifecycle from data exploration to deployment using Azure ML Studio, covering algorithm selection, model evaluation, and automated pipelines.

• Coursera
• 7 hours 49 minutes
• Self-Paced
• Paid Course

Coursera

Building, Optimizing, and Validating Machine Learning Models

Master building, optimizing, and validating ML models using hyperparameter tuning, cross-validation, SHAP explanations, and automated pipelines for efficient, reproducible workflows.

• Coursera
• 12 hours 9 minutes
• Self-Paced
• Paid Course

Coursera

Engineer & Explain AI Model Decisions

Discover how to build trustworthy AI systems by mastering feature engineering, model interpretability, and bias detection for ethical deployment in production environments.

• Coursera
• 3 hours 47 minutes
• Self-Paced
• Paid Course

Coursera Credential

Machine Learning Made Easy for Software Engineers

Master the full ML lifecycle—from training and optimizing models to deploying production-ready microservices—with hands-on projects covering pipelines, monitoring, and debugging.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 4 courses