AI-Data Analyst - Rooman Technologies

AI-ML Engineer

AI-ML Engineer - A fast track to the success.
100% Placement Assistance | 1000+ Hiring Partners
6734 Learners Enrolled

Program Duration : 390 Hrs

At 15 - 20 hrs/week

Classroom Based

Learning format

Branches Across India

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About Program

The “AI – Machine Learning Engineer” program trains individuals for roles in the IT-ITeS sector, focusing on AI, Big Data Analytics, product engineering, software development, and workplace management. Participants gain competencies in employing development tools, effective collaboration, and maintaining health and safety standards. The program equips them to understand business requirements, create compelling data-driven narratives, and collaborate with Data Scientists in complex model development. Upon completion, they master data inspection, transformation, statistical analysis, visualization, and machine learning, becoming adept at supporting strategic decision-making within the business intelligence landscape.


  • B.E./ B.Tech. – Computer Science, IT, Electronics or equivalent
  • MCA, MBA or Masters in Quantitative Subject
  • Working Professional in IT aspiring to start a career in Data Science

Key Benefits

  • Data Architecture
  • Data Management
  • Data Quality Assurance
  • Statistical Analysis
  • Machine Learning Techniques
  • Time Series Analysis
  • Text Analytics
  • Data Visualization & Methods

Course Curriculum

  • Overview of AI & Big Data Analytics and their societal impact
  • Roles and career paths in AI & Big Data Analytics
  • Key responsibilities of a Machine Learning Engineer
  • Skills and behaviours expected from a Machine Learning Engineer
  • Growth opportunities in the field
  • Idea Prioritization
  • Stages of Development
  • Feasibility and Planning
  • Competitive Advantage
  • Programming Practices
  • Automation and Scripting
  • Tools Utilization
  • System Configuration
  • Software Development Needs
  • System Limitations
  • Data Flows
  • Performance Evaluation
  • Algorithm Efficiency
  • Technical Specifications
  • Requirement Translation
  • Parallel Programming
  • Development Tools
  • Testing and Refinement

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