Our comprehensive ML training program covers:
1. Introduction to Machine Learning & AI
• Understanding the role of ML in AI applications.
• Differences between ML, Deep Learning, and Data Science.
2. Data Preprocessing & Feature Engineering
• Data cleaning, normalization, and feature selection techniques.
• Handling big data and unstructured datasets.
3. Supervised & Unsupervised Learning
• Building classification, regression, and clustering models.
• Training ML models using Python, Scikit-learn, and TensorFlow.
4. Deep Learning & Neural Networks
• Implementing CNNs for image recognition and RNNs for NLP.
• Exploring transformer models like GPT for text generation.
5. Cloud & Scalable ML Models
• Deploying ML models on AWS, Google Cloud, and Azure ML.
• Understanding MLOps and model monitoring.
6. Hands-On Projects & Real-World Applications
• AI use cases in finance, healthcare, retail, and smart cities.
• Developing a machine learning portfolio for career advancement.
By the end of the course, you will build, train, and deploy ML models confidently.