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Course Highlights

  • Builds strong fundamentals in Gen AI and LLMs to enhance Data Analytics workflows, including summarisation, insight generation and automated reporting.
  • Demonstrates how open-source models (LLaMA, Mistral, Falcon) can be applied to business analytics use cases such as decision support, dashboard narration and customer intelligence.
  • Establishes the foundation for applied AI systems - agents, retrieval pipelines and AI-powered business tools covered later in the certification.
  • Delivered with AlmaBetter’s best-in-class ecosystem - mentorship support, placement assistance, structured assignments and guided project reviews ensuring real outcomes.
  • Prepares learners for high-impact roles such as Business Analyst with Gen AI skills, AI-enabled Data Analyst, Applied AI Associate and Analytics Operations Specialist.
  • Eligible for Govt. of India incentives.

  • Skill Type

  • Course Duration

  • Domain

  • GOI Incentive applicable

  • Course Category

  • Nasscom Assessment

  • Placement Assistance

  • Certificate Earned

  • Badge Earned

  • Content Alignment Type

  • NOS Details

  • Mode of Delivery

Course Details

Learning Objectives

What will you learn in the Advanced Certification in Data Analytics & Gen AI Engineering Course?

By the end of this course, learners will be able to:

  • Use prompting techniques to automatically generate insights from datasets such as summarising trends, explaining KPIs and rewriting findings into business-ready narratives.
  • Build simple Gen AI-powered analytical helpers such as a report explainer, data-insight generator or customer query summariser.
  • Apply open-source models (LLaMA, Mistral and Falcon) for tasks such as extracting information from text, classifying responses or generating structured outputs for dashboards.
  • Convert raw business text - emails, survey responses and call transcripts - into sentiment‑based summaries and categorised insights.
  • Perform responsible-usage checks by detecting biased outputs, validating responses against data context and refining prompts to improve factual correctness.
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Reasons to enrol

Why should you take the Advanced Certification in Data Analytics & Gen AI Engineering Course?

  • Stay ahead of the curve as companies adopt Gen AI-driven analytics and business automation.
  • Build next-generation skills combining data analysis, Gen AI reasoning and intelligent insight generation.
  • Gain an edge in hiring for roles that increasingly expect AI-assisted workflows, not just spreadsheets and dashboards.
  • Learn how to automate reporting, summarisation and data interpretation - skills directly valuable in fast‑growing tech and consulting teams.
  • Position yourself for future roles where analytical thinking, AI tooling and business storytelling intersect.
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Ideal Participants

Who should take the Advanced Certification in Data Analytics & Gen AI Engineering Course?

  • Undergraduate or postgraduate learners aiming for careers in Data Analytics, Business Analytics or Applied AI roles.
  • Early-career professionals who want to upgrade analytical workflows using Gen AI tools and automation.
  • Working analysts, interns, or fresh graduates preparing for roles that require data interpretation, AI-based reporting and business insight generation.
  • Educators or faculty members who want to introduce practical Gen AI-based analytics concepts into their curriculum.
  • Enthusiasts and career-switchers seeking clarity on how AI models transform raw information into meaningful business outcomes.
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Curriculum

Curriculum

Advanced Certification in Data Analytics and Gen AI Engineering delivers a structured three-track curriculum: Data Analytics, Business Intelligence, and Applied Gen AI, building practical skills through guided assignments, interactive exercises, and hands-on, industry‑oriented projects.

  • Core Track: Data Analytics
    Python and Data Foundations
    Programming for analytics, OOP fundamentals, control flow, error handling, reusable functions, automation principles
  • Data Handling and Processing
    NumPy arrays, Pandas dataframes, joins, grouping, filtering, missing-value treatment, feature formatting
  • Exploratory Data Analysis and Business Insight
    Trend identification, segmentation, descriptive summaries, storyline-based reporting
  • Applied Data Workflows
    API-based data extraction, CSV/JSON ingestion, transforming raw sources into usable datasets
  • Interactive Data Applications
    Building insight dashboards using Streamlit, exporting visual narratives for stakeholders
  • Advanced Track: Business Intelligence
    Database and Analytical Querying
    Advanced SQL functions, multi-table joins, window operations, schema planning, query optimisation
  • Data Engineering Essentials
    ETL automation, dimensional modelling, partitioning, scheduling, and pipeline monitoring
  • Metric Design and KPI Frameworks
    Business performance metrics, funnel-based KPIs, conversion tracking, cohort-based decision mapping
  • BI Dashboarding and Reporting
    Power BI/Tableau dashboards, executive reporting layers, multi-sheet insights
  • Enterprise Data Environments
    Snowflake/BigQuery concepts, warehouse vs lake structures, collaborative BI workflows
  • Specialisation Track: Applied Gen AI Engineering
    Foundations of LLMs
    Tokenisation, embeddings, prompting structures, basic fine-tuning logic, model evaluation
  • Applied Prompt Engineering
    Templates for KPI explanation, summary generation, customer feedback structuring, business query reasoning
  • RAG-based Analytics Applications
    Document search, contextual retrieval, business data augmentation, reasoning-based responses
  • Multi-agent Orchestration
    Task assignment, tool-calling patterns, multi-step workflows, decision-driven automation
  • Deployment and Monitoring
    Containerised deployment, CI/CD for AI projects, usage evaluation, error-handling workflows
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skills and tools

Tools you will learn in the Advanced Certification in Data Analytics and Gen AI Engineering Course

Tools You Will Learn

  • Python and Analytics Stack - NumPy, Pandas, Matplotlib, Seaborn
  • SQL Workbench and Cloud Databases - MySQL/PostgreSQL, Snowflake, BigQuery
  • BI and Reporting Tools - Power BI, Tableau, Streamlit dashboards
  • Gen AI and LLM Frameworks - LangChain, Hugging Face, OpenAI APIs
  • Versioning and Deployment Tools - GitHub, Docker, CI/CD workflows

Skills You Will Develop

  • Performing end-to-end data analysis—cleaning, transforming, visualising, and deriving business insights
  • Writing advanced SQL queries for real-world datasets and reporting pipelines
  • Designing KPI-based dashboards for decision-making across business functions
  • Building RAG workflows, AI-assisted insight generators, and lightweight analytical agents
  • Fine-tuning prompts for business reasoning, summarisation, sentiment analysis, and trend narration
  • Deploying analytics and Gen AI applications with structured workflows and monitoring
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