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Fellowship Program in NextGen Data Analytics & Data Science with AI

With businesses increasingly relying on data-driven decision-making, professionals who can analyze data and build intelligent models are in high demand. Progress seamlessly from Data Analytics to Data Science with AI, with expert career guidance to build a successful career in the Data Science Field.

Crio Grads have Cracked their Dream Careers In

Technologies You'll Master

The full AI-native data stack

Across analytics, machine learning, and GenAI — the same stack used by Netflix, Uber, and OpenAI engineering teams.

Data Analytics & BI

Data Analytics & BI

Query, transform, visualize
SQLPythonPandasTableauPower BIExcelSeabornNumPy
Machine Learning & MLOps

Machine Learning & MLOps

Modeling at scale
Scikit-LearnTensorFlowPyTorchMLflowXGBoostAirflowSparkDocker
GenAI & Agentic AI

GenAI & Agentic AI

The new differentiator
ChromaDBPineconeLLM APIsRAGLangChainMultimodal

Master Data Insights with
Key Analytics Tools

Learn 25+ industry-relevant tools across data analytics, data science, and AI.

Data Analytics & BI
Python & Data Science
GenAI & LLM Stack
Cloud, MLOps & Big Data

Master Data Analytics &
Data Science with AI Skills

The work-experience-based approach that turns learners into job-ready data professionals — projects, mentorship, support and end-to-end skills.

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Exclusive Career Services
Mock interviews, resume building, and focused career assistance to crack Data analytics and Data science roles

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10+ work-like projects & 20+ micro skilling exercises
AI-driven industry-relevant projects and case studies across Data Analytics and Data Science to tackle real-world challenges

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80+ live guided sessions
Mentorship by Data Science & AI experts from leading tech companies

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Live chat support and dedicated success managers
12+ hours of daily live technical support to ensure a smooth & effortless learning experience

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200+ SQL problems & 200+ Python challenges
Build querying skills and data visualisation skills with tools like Tableau, Power BI, Seaborn, Scikit-Learn, OpenAI, MLflow

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End-to-End Data Science & AI
Build and deploy ML models, work with end-to-end data pipelines, and learn ML Ops and Big Data concepts used by Data scientists.

Work-like Projects & 20+ Micro-Skilling Exercises
10+

Work-like Projects & 20+ Micro-Skilling Exercises

Live Guided Sessions by Industry Experts
80+

Live Guided Sessions by Industry Experts

Hours of Daily Live Technical Support
12+

Hours of Daily Live Technical Support

SQL and Python Problems
400+

SQL and Python Problems

Crio vs. traditional data courses

See why Crio's AI-native, project-led model produces job-ready data scientists where others produce certificate holders.

A table displaying different course USPs, illustrating how Crio.Do's Data Analytics & Data Science Program excels compared to competitors.

Recruiters too, look for real project experience when hiring tech professionals and here at Crio, we strive to provide just that. We empower learners with high-quality applied learning opportunities and build skills that translate into career growth and success.

Ship 10 industry-grade AI projects to your portfolio

Every module ends with a project that simulates what data scientists actually build at top product companies.

Choose Your Specialization

Two AI-powered tracks. One world-class outcome.

Pick a path based on the role you're chasing. Both share the AI-native foundation; the focus differs.

OPTION 1 - DATA ANALYST

Data Analyst Track

Data / Business Analyst · BI Engineer

A 6-month AI-augmented track focused on extracting business value from data — fastest path to your first data role.

Advanced SQLPythonPower BITableau
  • Statistics & A/B testing for product decisions
  • GenAI copilots for analytics & data storytelling
  • 5 work-like projects + capstone
  • Target CTC8–14 LPA
★ Most PopularOPTION 2 - DATA SCIENTIST

Data Scientist (AI Track)

Data Scientist · ML Engineer · AI Engineer

A 9–10-month deep dive into machine learning, MLOps and GenAI/agentic systems — built for premium data science roles.

GenAIRAGLangChainMulti-agent systems
  • Everything in Analyst Track + advanced ML
  • MLOps: MLflow, Docker, model monitoring
  • 10+ AI projects · system design for ML
  • Target CTC12–26 LPA

You can explore both paths during early phases before locking in your specialization with the help of your mentor.

The curriculum to crack AI-era data jobs

Designed and taught by senior data scientists shipping ML and GenAI in production. Updated quarterly.

Premium

Advanced

Premium Curriculum (Included)

All 7 foundation modules from the Premium track

  • Establish a strong Python programming foundation for your data analytics career.
  • Master Python syntax, data structures, control flow, functions, modules and file handling.
  • Build reusable, modular code with Object-Oriented Programming principles.
  • Handle errors and exceptions gracefully and work with libraries effectively.
  • Invoke APIs, parse JSON and apply Statistics & Probability for data work.
Python Foundations
Data Structures
Control Flow
Functions
Modules
File Handling
Libraries
Error Handling
OOP
API Invocation
JSON
Statistics
Probability
  • Master SQL queries, joins and query optimization to extract data from relational databases.
  • Use Excel formulas, Pivot tables and lookup tables for analysis.
  • Manipulate and clean data programmatically with Pandas and NumPy.
  • Visualize data with Matplotlib, Seaborn, Power BI and Tableau dashboards.
  • Apply data storytelling techniques to communicate insights to business stakeholders.
SQL
Joins
Excel
Pivot Tables
Pandas
NumPy
Matplotlib
Seaborn
Power BI
Tableau
  • Tackle 10+ work-like projects modeled on real problems at top product companies.
  • Complete 20+ micro-skilling exercises that build muscle memory across the toolchain.
  • Work on AI-driven, industry-relevant case studies across analytics & data science.
  • Build a portfolio of shipped projects designed to showcase real-world data thinking.
Case Studies
Industry Projects
Business Insights
Data Storytelling
  • Solve 200+ Python challenges curated for data-role interviews.
  • Build pattern-based problem-solving skills across arrays, strings, hash maps and trees.
  • Practice mentor-reviewed solutions and AI-mock-tested challenges.
  • Strengthen the algorithmic thinking required for top-tech technical screens.
DSA
Problem Solving
Python Challenges
  • Build supervised, unsupervised and recommender systems with Scikit-Learn.
  • Apply GenAI workflows to analytics — RAG retrieval, prompt engineering, LLM evaluation.
  • Deploy models with MLflow experiment tracking and Dockerised serving.
  • Monitor production models for drift, accuracy and data quality.
Scikit-Learn
OpenAI
MLflow
RAG
Prompt Engineering
Model Deployment
  • Work with the Hadoop & Spark ecosystem and modern Data Lake/Warehouse patterns.
  • Build ETL/ELT pipelines that scale to 100M+ rows.
  • Orchestrate jobs with Airflow and stream events with Kafka.
  • Apply cost-aware design when querying and storing large datasets.
Apache Spark
PySpark
Airflow
Kafka
ETL
Data Warehousing
  • Prepare with focused interview prep, mock interviews and aptitude assessments.
  • Practice the most commonly asked technical questions for Data Analyst & DS roles.
  • Take part in timed mock interviews and real-world take-home assignments.
  • Build confidence with AI-driven mock sessions tuned to AI integration & problem-solving.
Conceptual Interview Prep
Take-Home Challenges
Mock Interviews

Advanced Add-ons

Seven Additional modules — exclusive to the Advanced track

The Advanced track is built for analysts targeting senior data and AI roles. It layers advanced Machine Learning, GenAI & LLM applications, and end-to-end analytics projects on top of the Premium foundation.

  • Master SQL queries, subqueries, and Joins to extract data from relational databases.
  • Understand data aggregation (GROUP BY) and query optimization best practices.
  • Gain expertise in Excel formulas, lookup tables, and Pivot tables for analysis.
  • Learn the role of KPIs and Metrics in solving real-world business problems.
  • Become familiar with various data formats like JSON, XML, and CSV.
  • Create charts and dashboards in Excel to visualize data insights.
  • Get hands-on experience with real-world datasets and schema diagrams.
SQL Queries
Joins
Query Optimization
Excel
Metrics
Data Aggregation
Pivot Tables
JSON/XML
Data Manipulation
Database Design
Data Schemas
  • Master Python syntax, control flow (loops/conditionals), and data structures (Lists/Dicts).
  • Write reusable code using Functions, Modules, and Object-Oriented Programming (OOP).
  • Handle errors and exceptions gracefully within applications.
  • Learn to use Python libraries and file handling techniques.
  • Solve commonly asked coding problems to build algorithmic thinking.
Python Foundations
OOP
Data Structures
Control Flow
Statistics
Probability
Error Handling
Libraries
GenAI-Assisted Coding
Computational Thinking
  • Master NumPy and Pandas for high-performance data manipulation and cleaning.
  • Perform Exploratory Data Analysis (EDA) including univariate and multivariate analysis.
  • Visualize data programmatically using Matplotlib and Seaborn.
  • Connect Python to SQL databases to fetch and process raw data.
  • Master Business Intelligence tools like Power BI and Tableau for dashboarding.
  • Apply data storytelling techniques to communicate insights effectively.
  • Projects: QSales (Smart Sales Forecaster), Flipkart/Stock Dashboards.
Pandas
NumPy
Matplotlib
Power BI
Tableau
Data Cleaning
Story-telling
SQL Integration
EDA
Hypothesis Testing
Inferential Statistics
  • Master Linear Algebra, Calculus, and Statistics for AI — distributions, Bayes' Theorem, and Hypothesis Testing.
  • Build ML pipelines: Preprocessing, Feature Engineering, Dimensionality Reduction (PCA), and Version Control (DVC).
  • Implement Supervised & Unsupervised algorithms — Regression, Trees, Random Forest, SVM, and Clustering.
  • Train and tune models with Scikit-learn & XGBoost — Cross Validation, Hyperparameter search, and SHAP.
  • Evaluate models (Precision/Recall, ROC-AUC), handle imbalanced data, and apply AI Ethics & Responsible AI.
  • Projects: QFactory (Predictive Maintenance) & QTraffic (Accident Risk Predictor).
Supervised Learning
Regression
Classification
Clustering
Scikit-learn
Feature Engineering
XGBoost
Ensemble Learning
PCA
Cross Validation
Hyperparameter Tuning
SHAP
  • Master Big Data (Hadoop, Spark) with Spark optimization and MLlib at scale, on Lake/Warehouse architectures.
  • Build scalable ETL/ELT and real-time streaming pipelines with PySpark, Kafka, and Airflow.
  • Deploy models with Docker, FastAPI, and CI/CD — Batch/Real-time serving and deployment strategies.
  • Monitor in production with Grafana, Drift Detection, and Experiment Tracking & Model Registry (MLflow).
  • Work with Cloud (AWS/GCP) and NoSQL, with automated testing and data-quality gates.
  • Projects: QFactory (Production Monitoring) & QTrend (Social Media Data Pipeline).
PySpark
Kafka
Airflow
ETL
CI/CD
MLOps
Model Serving
Drift Detection
MLflow
NoSQL
Docker
FastAPI
Grafana
  • Build the foundation: Neural Networks, NLP & embeddings, Transformers, and LLM training (pre-training, RLHF).
  • Build AI Agents & Agentic AI — tool use, function calling, and multi-step reasoning.
  • Architect GenAI apps with RAG, Vector Databases, LangChain, and LLM APIs.
  • Advanced Prompt Engineering, Multimodal AI (Whisper, vision), and LLM Evaluation with Safety Guardrails.
  • Optimize with Ensembles and Time-Series forecasting; deploy on Kubernetes, Kubeflow & Cloud ML (SageMaker, Vertex AI).
  • Projects: QResume & QCoach; QAudio (Deep Learning Optimization).
Generative AI
RAG Architectures
Prompt Engineering
Transformers
Deep Learning
LLM Evaluation
Kubernetes
Agentic AI
AI Agents
Multimodal AI
Vector Databases
Time-Series Forecasting
Model Optimization
  • Prepare to succeed in data science interviews with focused interview preparation, mock interviews, and aptitude assessments.
  • Perfect your interview skills for Data Scientist roles through multiple AI-driven practice sessions.
  • Practice the most commonly asked technical questions, including logic building and data manipulation challenges, to ace your interview.
  • Take part in timed mock interviews and solve take-home assignments focused on real-world data problems and AI applications.
  • Build confidence for upcoming interviews by engaging in mock sessions, focusing on AI integration and problem-solving techniques.
Conceptual Interview Questions Prep
Take-Home Challenges
AI Mock Interviews

Where AI shows up in
your data work

Six concrete AI-native applications you'll build across the Data Analytics and Data Science curriculum.

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Text-to-SQL for Business Analysis

Build systems that turn plain-English business questions into validated SQL, run them against production databases, and explain the results back to stakeholders.

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AI-Powered EDA & Data Cleaning

Use LLMs to profile new datasets, surface data-quality issues, and draft cleaning strategies for downstream analytics and ML pipelines.

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Storytelling Dashboards

Layer LLMs on top of Power BI and Tableau so non-technical stakeholders can ask questions of data and get narrated insights, not just charts.

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RAG-Powered Knowledge Systems

Design retrieval pipelines over internal docs, tickets, and product specs so any stakeholder gets cited, source-grounded answers to their questions.

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Agentic AI for Data Workflows

Build LangChain agents that use tools, call functions, and reason through multi-step data tasks — monitoring metrics, triggering retraining, and alerting on anomalies.

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Multimodal AI Products

Combine Whisper (audio), vision models, and LLMs to build data products that ingest text, image, and audio inputs — bridging classic DS with modern GenAI.

Graduates landing 10–26 LPA AI-data roles

Numbers verified by an independent placement audit, refreshed every cohort.

Placed Within 9 Months
93%

Placed Within 9 Months

Avg dream-job CTC
10 LPA

Avg dream-job CTC

Avg super-dream CTC
21 LPA

Avg super-dream CTC

Average Salary Hike
81%

Average Salary Hike

What Our Graduates Say

Real experiences from professionals who transformed their careers.

Get more insights on how Crio can help you crack a data analytics role in top tech companies.

Learn from Industry Experts

Your mentors are shipping AI products at scale


Komal Sharma
Komal Sharma
Software Engineer
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Sameer Pratap Singh
Sameer Pratap Singh
Senior Software Engineer
Sameer Pratap Singh's company logo
LinkedIn logo
Ayush Agarwal
Ayush Agarwal
Software Engineer
Ayush Agarwal's company logo
LinkedIn logo
Ankit Mishra
Ankit Mishra
Software Engineer
Ankit Mishra's company logo
LinkedIn logo
Syed Abbas
Syed Abbas
Software Developer
Syed Abbas's company logo
LinkedIn logo
Mohit Kamal
Mohit Kamal
Senior Frontend Engineer
Mohit Kamal's company logo
LinkedIn logo
Niteen Sampat Ghodke
Niteen Sampat Ghodke
Java Full Stack Corporate Trainer
Niteen Sampat Ghodke's company logo
LinkedIn logo
Raajavel
Raajavel
Senior SRE
Raajavel's company logo
LinkedIn logo
Sreeja Paluvatla
Sreeja Paluvatla
Lead Tech Mentor
Sreeja Paluvatla's company logo
LinkedIn logo
Ajo John
Ajo John
Lead Member of Technical Staff
Ajo John's company logo
LinkedIn logo
Aditya Singh
Aditya Singh
Developer Experience Engineer
Aditya Singh's company logo
LinkedIn logo
Dushyanth
Dushyanth
Research Analyst
Dushyanth's company logo
LinkedIn logo
Mohit Kamal
Mohit Kamal
Software Engineer
Mohit Kamal's company logo
LinkedIn logo
Ramesh Vaka
Ramesh Vaka
Senior Project Manager
Ramesh Vaka's company logo
LinkedIn logo
Jarugu Ganesh Kumar
Jarugu Ganesh Kumar
Software Engineer
Jarugu Ganesh Kumar's company logo
LinkedIn logo
Komal Sharma
Komal Sharma
Software Engineer
Komal Sharma's company logo
LinkedIn logo
Sameer Pratap Singh
Sameer Pratap Singh
Senior Software Engineer
Sameer Pratap Singh's company logo
LinkedIn logo
Ayush Agarwal
Ayush Agarwal
Software Engineer
Ayush Agarwal's company logo
LinkedIn logo
Ankit Mishra
Ankit Mishra
Software Engineer
Ankit Mishra's company logo
LinkedIn logo
Syed Abbas
Syed Abbas
Software Developer
Syed Abbas's company logo
LinkedIn logo
Mohit Kamal
Mohit Kamal
Senior Frontend Engineer
Mohit Kamal's company logo
LinkedIn logo
Niteen Sampat Ghodke
Niteen Sampat Ghodke
Java Full Stack Corporate Trainer
Niteen Sampat Ghodke's company logo
LinkedIn logo
Raajavel
Raajavel
Senior SRE
Raajavel's company logo
LinkedIn logo
Sreeja Paluvatla
Sreeja Paluvatla
Lead Tech Mentor
Sreeja Paluvatla's company logo
LinkedIn logo
Ajo John
Ajo John
Lead Member of Technical Staff
Ajo John's company logo
LinkedIn logo
Aditya Singh
Aditya Singh
Developer Experience Engineer
Aditya Singh's company logo
LinkedIn logo
Dushyanth
Dushyanth
Research Analyst
Dushyanth's company logo
LinkedIn logo
Mohit Kamal
Mohit Kamal
Software Engineer
Mohit Kamal's company logo
LinkedIn logo
Ramesh Vaka
Ramesh Vaka
Senior Project Manager
Ramesh Vaka's company logo
LinkedIn logo
Jarugu Ganesh Kumar
Jarugu Ganesh Kumar
Software Engineer
Jarugu Ganesh Kumar's company logo
LinkedIn logo
Komal Sharma
Komal Sharma
Software Engineer
Komal Sharma's company logo
LinkedIn logo
Sameer Pratap Singh
Sameer Pratap Singh
Senior Software Engineer
Sameer Pratap Singh's company logo
LinkedIn logo
Ayush Agarwal
Ayush Agarwal
Software Engineer
Ayush Agarwal's company logo
LinkedIn logo
Ankit Mishra
Ankit Mishra
Software Engineer
Ankit Mishra's company logo
LinkedIn logo
Syed Abbas
Syed Abbas
Software Developer
Syed Abbas's company logo
LinkedIn logo
Mohit Kamal
Mohit Kamal
Senior Frontend Engineer
Mohit Kamal's company logo
LinkedIn logo
Niteen Sampat Ghodke
Niteen Sampat Ghodke
Java Full Stack Corporate Trainer
Niteen Sampat Ghodke's company logo
LinkedIn logo
Raajavel
Raajavel
Senior SRE
Raajavel's company logo
LinkedIn logo
Sreeja Paluvatla
Sreeja Paluvatla
Lead Tech Mentor
Sreeja Paluvatla's company logo
LinkedIn logo
Ajo John
Ajo John
Lead Member of Technical Staff
Ajo John's company logo
LinkedIn logo
Aditya Singh
Aditya Singh
Developer Experience Engineer
Aditya Singh's company logo
LinkedIn logo
Dushyanth
Dushyanth
Research Analyst
Dushyanth's company logo
LinkedIn logo
Mohit Kamal
Mohit Kamal
Software Engineer
Mohit Kamal's company logo
LinkedIn logo
Ramesh Vaka
Ramesh Vaka
Senior Project Manager
Ramesh Vaka's company logo
LinkedIn logo
Jarugu Ganesh Kumar
Jarugu Ganesh Kumar
Software Engineer
Jarugu Ganesh Kumar's company logo
LinkedIn logo

Exclusive Career Services - With a personalized Career Plan

Get access to Crio’s Exclusive Career Services that will equip you to use your learnings and skills to land your next job.

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1:1 Interview preparation including 10 AI Mock Interviews before technical interview rounds.

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Soft-Skills training coupled with pre-training and post-training assessments

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Series of mock assessments and detailed interview prep sprints to ace top tech jobs

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Expert guidance to get your profile ready (Github, Portfolio, LinkedIn, Resume)

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Access to a diverse set of job opportunities with 1000+ hiring partners

Program Fee and Scholarships

EMI as low as

7,874

/month

(For 36 months)

Before Scholarship
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A Free Trial Session

No Fee Required

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Assured Scholarships

After Free Trial

12 month no-cost EMI and 18, 24 & 36 month low-cost EMI available.

FAQs

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