Gut feel still drives decisions while models sit unused in notebooks. Hands-on Python, machine learning, and MLOps training turns data into forecasts and choices the business will use.

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Training modules in

Data Science

AI and MLOps Fundamentals

Build a strong foundation in designing, developing, and deploying AI and ML models from initial scoping to production. Learn how to optimize model performance, address scaling challenges, and collaborate across teams to deliver reliable, high ROI AI solutions.

AI for Everyone

Build a strong foundation in AI, Machine Learning, and Data Science to understand core concepts, real world applications, and how AI projects are delivered in organizations. Learn how to assess business impact, define AI strategy, collaborate across teams, and address ethical considerations in AI adoption.

Apache Spark with Scala

Build a strong foundation in big data processing using Apache Spark and Scala by understanding Spark architecture and core APIs. Learn how to process large datasets, apply advanced analytics and streaming, optimize performance, and integrate Spark with diverse data sources for scalable data driven solutions.

Computational Mathematics for Data Science

Build a strong foundation in statistics and machine learning for data science, covering probability, distributions, and hypothesis testing. Learn how to apply regression techniques, decision trees, and statistical methods to analyze data and support informed business decisions.

Data Mining for Business

Build a strong foundation in data mining by understanding end to end processes, techniques, and algorithms. Learn how to apply classification, clustering, association, and text mining methods using R or Python, and effectively interpret and communicate insights for real world business problems.

Data Science with Machine Learning

Build a strong foundation in data science and machine learning by mastering core concepts, algorithms, and data analysis techniques. Learn how to build, evaluate, and scale production ready predictive models using modern tools and frameworks for real world business applications.

Data Science with Python

Build a strong foundation in Python for data analysis and machine learning by learning core programming concepts and visualization techniques. Gain hands on experience with real world examples and popular Python frameworks to build and apply machine learning models effectively.

Data Science with R Programming

Build a strong foundation in data science using R by mastering data analysis, visualization, and statistical modeling techniques. Learn how to build predictive models, apply machine learning, and communicate data driven insights effectively to support informed business decisions.

Generative AI

Build a strong foundation in Generative AI by understanding its core concepts, tools, and platforms. Learn how to apply generative AI across business use cases, master prompt engineering, and address ethical considerations to responsibly integrate generative AI into real world operations.

MLOps, LLMOps & AI Deployment Engineering (Advanced)

Take your AI from notebooks to production-grade ML & GenAI systems

Natural Language Processing in Data Science

Build a strong foundation in Natural Language Processing by understanding core concepts, techniques, and real world applications. Learn how to design, implement, evaluate, and integrate NLP solutions using modern libraries while customizing models to meet domain specific business needs.

Predictive Modeling in Data Science

Build a strong foundation in predictive modeling by understanding core concepts, algorithms, and real world applications. Learn how to preprocess data, engineer features, evaluate models, and build accurate predictive solutions using Python or R for data driven decision making.