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AI/ML Program

Mastering Machine Learning

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Machine Learning Program

From Basics to Enterprise Excellence

Transform your AI career with EdAthena's comprehensive Machine Learning Program, offering three distinct learning tracks tailored to your expertise level. Our curriculum combines theoretical knowledge with hands-on experience, preparing you for real-world AI challenges.

Program Highlights:

  • Foundation Track (8 weeks): Build a strong foundation in Python, data manipulation, visualization, and basic ML models
  • Advanced Track (12 weeks): Master scalable solutions using cloud platforms, MLOps pipelines, and advanced deployment strategies
  • Expert Track (20 weeks): Achieve expert-level proficiency in enterprise AI development, advanced architecture, and production-grade systems

What Sets Us Apart:

  • Hands-on experience with 50+ industry-relevant projects
  • Mastery of cutting-edge tools: TensorFlow, PyTorch, Docker, Kubernetes, MLflow, and LangChain
  • Complete MLOps lifecycle training from development to production
  • Strong focus on AI ethics and responsible development practices
  • Real-world applications across cloud platforms (AWS, GCP, Azure)

Whether you're starting your AI journey or aiming for enterprise-level expertise, EdAthena provides a structured pathway to success. Our program emphasizes practical skills, ethical considerations, and industry best practices, preparing you to lead and innovate in the rapidly evolving field of artificial intelligence.

Join EdAthena today and position yourself at the forefront of the AI revolution. Transform your career with a program that goes beyond traditional learning to deliver comprehensive, practical expertise in modern AI systems.

ML Courses

ML101 - ML Foundation

Level: Basic (L)
Duration: 12 Weeks
Fee: 20K
Method: Online, Live Sessions

Topics covered:

  • ML Foundation
    • Data Manipulation
    • Basic neural networks, TensorFlow and PyTorch
    • ML Model Visualization
    • Deep Learning Basics

ML201 - ML Advanced

Level: Intermediate (M)
Duration: 16 Weeks
Fee: 25K
Method: Online, Live Sessions

Topics covered:

  • ML Algorithms and Optimization
    • Advanced ML Algorithms
    • Deep Learning Advanced
    • Model Optimization & Deployment
    • MLOps Fundamentals

ML301 - ML Expert

Level: Advanced (H)
Duration: 20 Weeks
Fee: 30K
Method: Online, Live Sessions

Topics covered:

  • ML Architecture
    • Advanced ML System Architecture
    • Container Orchestration & Distributed Computing
    • Advanced MLOps & Monitoring
    • Enterprise ML System Integration


What you will learn ?

Foundation Level (ML101)

12 Weeks
+
  • Development Environment Setup: Python core concepts, Jupyter Notebooks configuration, and fundamental programming exercises
  • Data Processing Fundamentals: NumPy operations and Pandas for efficient data manipulation and cleaning
  • Data Visualization & ML Foundations: Matplotlib/Seaborn for insights and introduction to Scikit-learn
  • Deep Learning Introduction: TensorFlow/PyTorch basics, neural networks architecture, and model training principles
  • Project Implementation: End-to-end ML project development integrating all tools and frameworks
  • Data Preprocessing: Advanced techniques for data cleaning, transformation, and feature engineering
  • Model Training & Evaluation: Best practices for model development, validation, and performance optimization
  • Development Tools Mastery: Version control, documentation, and collaborative development workflows
  • ML Infrastructure: Model deployment basics using TensorBoard and evaluation utilities

Advanced Level (ML201)

16 Weeks
+
  • Advanced Development Foundations: Git version control mastery, advanced Python concepts, and comprehensive ML toolkit integration (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch)
  • Cloud Infrastructure & Containerization: Docker implementation, cloud platform (AWS/GCP/Azure) fundamentals, and deployment strategies
  • MLOps Foundation: MLflow for experiment tracking, DVC for data versioning, and pipeline development essentials
  • Data Version Control: Advanced DVC implementations, dataset management, and versioning best practices
  • Workflow Orchestration: Airflow fundamentals, pipeline development, and workflow automation techniques
  • Time Series Analysis: Prophet and StatsModels implementation for advanced time series modeling and forecasting
  • Cloud Integration: Advanced cloud service utilization, multi-cloud strategies, and cloud-native ML deployments
  • Pipeline Development: Advanced orchestration with Airflow/Kubeflow, complex workflow management, and automation
  • Project Portfolio: Three comprehensive project implementations showcasing cloud integration and pipeline orchestration
  • Advanced MLOps: Integration of Docker, cloud services, MLflow, DVC, and workflow tools for production-grade ML systems

Expert Level (ML301)

20 Weeks
+
  • Advanced System Architecture: Integration of enterprise ML tools, advanced cloud orchestration, and comprehensive system design principles
  • Distributed Computing & Big Data: Kubernetes orchestration, Apache Spark processing, and Ray distributed computing implementation
  • Container Orchestration: Advanced Kubernetes deployment, cluster management, and scalable infrastructure design
  • API Development & Integration: FastAPI/Flask implementation, LangChain/LlamaIndex integration, and robust API architecture
  • Data Validation & Quality: Great Expectations implementation, advanced testing frameworks, and data quality assurance
  • Advanced MLOps & Monitoring: Weights & Biases integration, complex pipeline orchestration, and sophisticated monitoring systems
  • Enterprise System Design: Full-stack ML architecture, production deployment strategies, and system scaling
  • Production Infrastructure: Advanced Kubernetes features, complex data pipelines, and enterprise-grade monitoring
  • Large-Scale Data Processing: Distributed computing implementation, big data workflows, and scalable processing solutions
  • Enterprise Projects: Four complex project implementations demonstrating full-stack ML systems with production deployment
  • System Integration: Comprehensive integration of all tools including Kubernetes, Spark, Ray, FastAPI, LangChain, and W&B

Contact Information

Edathena Academy

CIIC, Crescent Engg. College
Vandalur, Tamil Nadu 600048

+91-98403-47570
eda@edathena.com

Operating Hours
Mon – Fri 9:00AM – 6:00PM

Connect With Us

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Recognition of Excellence

EdAthena awards verified Certificates of Completion to students who successfully finish their courses. Each certificate includes the learner's name, course details, lecture and practice hours, and a unique GUID for verification. Our certificates, recognized by employers and institutions, validate the learner's mastery of required skills through lectures, assignments, and evaluations.

Our certification program is designed in collaboration with industry experts and aligned with current market demands. Learners gain practical experience through hands-on projects and real-world applications, ensuring they're well-prepared for industry challenges. The certification not only demonstrates technical proficiency but also showcases problem-solving abilities and project implementation skills valued by employers.

Further information about course structure, prerequisites, and learning paths is available in our detailed course guide.

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