MLOps
How to Build a Production ML Pipeline in 2024
A step-by-step guide to setting up automated training, deployment, and monitoring using MLflow and Azure.
Mar 12, 2024·8 min read
Available for Corporate Training
Pavan
Khandare
AI Systems ArchitectMLOps EngineerLead Data Scientist
Get industry-ready AI jobs with real-world project experience.
Learn Data Science, GenAI, and MLOps the way companies actually build and deploy AI systems.
10,000+
Students Trained
50+
Corporate Projects
8+
Years Experience
Corporate & Academic
Trainer & Consultant
Scroll
Trusted By & Associated With
The Person Behind It
About Me
I am a Data Science Consultant and AI Systems Architect specializing in Machine Learning, Deep Learning, Generative AI, MLOps, and Cloud AI systems.
I focus on building real-world, production-ready AI systems that deliver measurable business impact. My expertise includes NLP, Computer Vision, Time Series Forecasting, Recommender Systems, and scalable AI infrastructure using Azure, AWS, and Spark.
I have trained 10,000+ students across corporate and academic environments and helped many learners transition into high-paying AI and Data Science roles through hands-on, real-world learning.
Signature Approach
I don't just build models
I build systems that work in the real world.
End-to-End Pipelines
ML Deployment & MLOps
Monitoring & Retraining
Cloud-Native Architecture
Why Us
Why this program gets you
job-ready faster
Most courses teach theory. I teach you how to build real AI systems used in industry.
Every module ends with a working, deployed project that you can showcase in interviews.
Build real software systems, not just run notebooks
End-to-end pipeline learning from data to deployment
Industry-focused curriculum updated every 6 months
Mentor-guided learning with working professionals
Job-ready portfolio with production-grade projects
No traditional theory-only teaching — 80% hands-on
CHOOSE YOUR PATH
Choose Your Path to a High-Paying AI Career
Master Data Analytics, Data Science, or Data Engineering with real-world, industry-ready training designed to get you job-ready faster.
Course 01
Data Analytics & Foundations
Start your journey with strong data analysis and business intelligence skills used in real companies.
Learn how to work with data from scratch — cleaning, analyzing, and visualizing it using industry tools.
What You Will Learn
Python (NumPy, Pandas)
SQL for Data Analysis
Data Cleaning & Preprocessing
Data Visualization (Matplotlib, Seaborn)
Power BI Dashboards
Exploratory Data Analysis (EDA)
Tools & Technologies
PythonSQLPower BIPandasNumPySeaborn
Foundation Level
Intermediate Level
Course 02
Data Science + Machine Learning + GenAI
Build intelligent AI systems using machine learning and modern Generative AI tools.
Learn how to create predictive models and AI applications used in real-world systems.
What You Will Learn
Machine Learning (Regression, Classification)
Deep Learning (Neural Networks)
Feature Engineering
Model Evaluation
Large Language Models (LLMs)
RAG Systems
Agentic AI (LangChain)
Tools & Technologies
Scikit-learnTensorFlowOpenAILangChainHuggingFace
Course 03
Data Engineering + MLOps + Cloud Deployment
Master how real companies deploy and scale AI systems using modern infrastructure.
Learn how to handle big data, automate pipelines, and deploy AI systems in production.
What You Will Learn
Apache Spark & Kafka
Airflow & dbt
MLOps (MLflow, DVC)
CI/CD for ML
Docker & Kubernetes
Azure ML & Deployment
Real-time data pipelines
Tools & Technologies
DatabricksAzure MLSparkKafkaDockerKubernetes
Advanced Level
Final Outcome
What You Will Achieve
Choose your path based on your course or master all three to become a complete AI professional.
Course 01
Data Analytics Path
- Become job-ready Data Analyst
- Work with real-world datasets
- Build dashboards & business insights
- Strong foundation for Data Science
Data Analyst
Course 02
Data Science & GenAI Path
- Become Data Scientist / AI Engineer
- Build Machine Learning & AI models
- Work with LLMs, RAG & GenAI tools
- Develop real-world AI applications
Data Scientist / AI Engineer
Course 03
Data Engineering & MLOps Path
- Become Data Engineer / MLOps Engineer
- Build scalable data pipelines
- Deploy AI systems in production
- Work with cloud & real-time systems
Data Engineer / MLOps Engineer
Salary Range
₹8–30 LPA
based on role, skills, and experience
Real Mentored Projects
Projects You Will Build
Production-level AI systems built by students under direct mentorship — from problem understanding to full deployment. These are what you'll create.
Healthcare AICerviShield
Cervical Cancer Detection & Prevention System
An AI-powered healthcare platform for early detection and risk prediction of cervical cancer using machine learning models built on real clinical datasets.
- End-to-end ML pipeline
- Deployed web application
- Real-world healthcare impact
Healthcare AIMomsFirstCare
Maternal & Child Healthcare Platform
A data-driven platform guiding mothers through pre-care and post-care stages with personalized insights, hospital integration, and real-world usability in India.
- Data-driven decision system
- User-focused healthcare platform
- Real-world application
Environmental AIEchoes of the Ganga
Data-Driven Environmental Analysis
A research and analytics platform analyzing pollution trends in the Ganga River using government datasets from 2000–2024 with predictive insights till 2030.
- Government data analysis
- Predictive insights (till 2030)
- Research + documentary integration
What Makes This DifferentNot just theory.
Not just theory.
Real systems. Real deployments.
Unlike traditional courses that focus only on theory or small projects, I mentor students to build real-world AI systems, fully deployed applications, and end-to-end solutions — from Data → Model → Deployment.
These projects represent the level of work you will be able to build during the program.
Your Outcome
By the end of the program, you will have:
Production-ready projects
A strong portfolio for interviews
Real-world problem-solving experience
Confidence to build and deploy AI systems independently
VIDEO SHOWCASE
See Real Work, Training & AI Concepts in Action
Watch real classroom sessions and in-depth explanations of machine learning, AI, and data science concepts using industry tools and real-world approaches.
Introduction
Machine Learning क्या है? | Complete Introduction in Hindi
A complete beginner-friendly introduction to Machine Learning — what it is, how it works, and where it's used in real-world AI systems.
All Videos
More project demos and training videos are updated regularly.
Subscribe to never miss a new lesson or concept breakdown.
Skills
Core Expertise
What you will master — skills companies actually hire for
AI Systems Architecture
Designing scalable, production-ready AI architectures that integrate seamlessly with enterprise infrastructure.
System DesignMicroservicesAPIs
MLOps & Deployment
Building end-to-end ML pipelines with CI/CD, model versioning, and automated retraining workflows.
MLflowDockerKubernetes
Generative AI & LLMs
Fine-tuning and deploying large language models, RAG systems, and agentic AI workflows for enterprise use.
LangChainOpenAIRAG
Azure ML & Cloud AI
End-to-end model lifecycle management on Azure ML, AKS, Databricks, and AWS SageMaker.
AzureAWSDatabricks
Data Engineering
Building scalable data pipelines using Spark, Kafka, dbt, and Airflow for reliable AI feature stores.
SparkKafkaAirflow
NLP & Computer Vision
Deploying transformers for text classification, entity extraction, image recognition, and object detection.
BERTYOLOHuggingFace
Time Series Forecasting
Production-grade demand forecasting, anomaly detection, and predictive maintenance at scale.
ProphetLSTMARIMA
AI Governance & Ethics
Implementing responsible AI practices, model explainability, bias detection, and compliance frameworks.
XAIFairnessCompliance
Corporate & Academic Impact
Industry & Academic Leadership
Corporate Training
Delivering AI, ML, GenAI, and MLOps training to companies for real-world business impact. Bridging the gap between academic knowledge and production systems.
Faculty Development
Training college faculty and bridging the industry-academia gap through structured FDP programs aligned with current industry needs.
Curriculum Design
Designing industry-aligned syllabuses for Data Science, AI, and Cloud programs adopted by engineering colleges and training institutes.
Career
Experience Timeline
2022 – Present
Lead Data Scientist
Clickflow
Leading AI systems design, NLP product development, and scalable data infrastructure to power growth analytics.
2020 – 2022
Sr. Data Science Consultant
3RI Technologies
Delivered corporate AI/ML training programs and consulted on enterprise AI strategy and deployment.
2019 – 2020
Consultant – AI & Data Science
Independent
Consulted for multiple startups on building ML-powered products, recommendation engines, and forecasting tools.
2018 – 2019
Data Science Associate
ActioHX
Built predictive models and data pipelines for healthcare analytics and patient outcome prediction systems.
2016 – 2018
Supply Chain Analyst
Entercoms
Applied data analytics to optimize supply chain operations, demand forecasting, and logistics efficiency.
Blog
Insights & Learning
Career
Data Scientist vs MLOps Engineer: Which Path in 2024?
Breaking down the skills, salaries, and day-to-day realities of two of the most in-demand AI roles.
Feb 28, 2024·6 min read
GenAI
RAG Systems Explained: Building Your Own Knowledge Base
How to implement Retrieval-Augmented Generation for enterprise use cases using LangChain and vector databases.
Jan 15, 2024·10 min read
Get Started
Ready to Start Your AI Career?
Join 10,000+ learners and build real-world AI skills with industry-focused training. Get mentored on projects that actually get you hired.
Contact
Get in Touch
Have questions about the courses, curriculum, or career path? Reach out and I'll personally guide you to choose the right program.