We are looking for Data Science Interns interested in working on AI, Machine Learning, and real-world projects.

This opportunity is best suited for candidates who are serious about building practical skills.

This program is aligned with tools and workflows used in modern companies:

Advanced Programming & Data Engineering Layer

Advanced Python (modular, scalable architecture)

Async programming for high-performance systems

Data pipelines using Pandas + Polars

Handling real-time & streaming data

Data versioning concepts (DVC basics)

Analytics + Decision Intelligence

Advanced EDA with business case mapping

Data storytelling for stakeholders

A/B testing & experimentation basics

KPI-driven analytics (how companies measure impact)

Machine Learning (Production-Level)

End-to-end ML pipelines (not just models)

Feature engineering for real-world problems

Model optimization & hyperparameter tuning

Handling imbalanced & noisy datasets

Model explainability (SHAP / LIME basics)

Generative AI Engineering

LLM APIs + open-source models (LLaMA, Mistral basics)

Prompt Engineering for production use

Retrieval-Augmented Generation (RAG systems)

Vector databases (FAISS / Chroma basics)

AI Agents (multi-step task automation)

Building real AI assistants & automation tools

Deep Learning (Applied AI Systems)

Transfer learning (real industry usage)

CNN for vision-based applications

NLP pipelines for real data

Using pre-trained models effectively

MLOps & AI System Design

Model deployment using FastAPI (modern standard)

Docker basics for AI applications

CI/CD concepts for ML workflows

Model monitoring & performance tracking

API-based AI architecture

Cloud & Scalable AI Systems

Deploying AI models on AWS / GCP / Azure

Serverless concepts (intro level)

Scalable AI application design

Cost-aware AI deployment (real company need)

Full-Stack AI Integration

AI + Backend (FastAPI / Django)

AI-powered web applications

Building SaaS-style AI tools

End-to-end system:

Data → Model → API → UI → Deployment

Real-World Engineering Practices

Git-based team workflows

Code reviews & version control

Writing production-level code

Debugging real project issues

Documentation like real companies

Flagship Real-World Projects You Will Build(Few List)

1. AI-Powered Business Assistant (LLM + RAG System)

Build a real AI assistant similar to tools used in companies:

Chatbot trained on custom business data





Uses LLM + Retrieval-Augmented Generation (RAG)

Stores knowledge using vector databases

Answers real queries like a company support system

What you learn:

Prompt Engineering

RAG architecture

Vector DB (FAISS/Chroma)

API-based AI deployment

2. End-to-End Data Analytics Dashboard (Business Use Case)

Work on a real dataset and build a complete analytics solution:

Data cleaning & transformation

KPI-based analysis

Interactive dashboard (Power BI / Tableau)

Business insights & reporting

What you learn:

Real-world EDA

Data storytelling

Decision-making using data

Industry-level reporting

3. AI-Based Prediction System with Deployment

Build a full ML system from scratch and deploy it:

Data preprocessing & feature engineering

Model building & optimization

API creation using FastAPI

Deploy as a usable web application

What you learn:

End-to-end ML pipeline

Model deployment

Real-world application usage

Production-level thinking

“All projects are designed to simulate real company-level workflows and will be part of your skilled portfolio.”

The above are representative flagship projects. Participants will be exposed to multiple industry-relevant problem statements and will work on similar real-world projects aligned with current industry demands.

What Makes This Program Different

Most courses focus on theory and predefined examples.

Here, you will:

Work on real-world problem statements

Build complete end-to-end projects

Handle real datasets (not just sample data)

Understand deployment and practical usage

Learn how Data Science is used in actual companies

Practical Exposure

Industry-style project workflows

Project documentation & presentation

AI model integration with web applications

Real-time problem solving

Who Should Apply

✔ Students (B.Tech / BSc / MSc / MCA / BCA / M.Tech)

✔ Fresh graduates

✔ Candidates who completed a course but lack confidence

✔ Individuals serious about Data Science / AI careers

What You Will Gain

Strong practical foundation in Data Science

Real-world project portfolio





Exposure to industry tools & workflows

Mentorship from experienced professionals

Career guidance & interview preparation

Program Details

Duration: 6 – 9 Months

Mode: Hybrid / On-site (Kochi)

Application Process (Strictly Followed)

Apply only through Indeed

Shortlisted candidates will be contacted via email

Job Type: Internship
Contract length: 6 months

Pay: From ₹1.00 per month

Application Question(s):

- This opportunity includes a structured training program followed by internship exposure. Are you comfortable enrolling in an internship training with a program cost before the internship phase?

Options:

Yes, I am comfortable with the training program

I would like more details about the program

No, I am only looking for a free internship

- Candidates who already have strong practical knowledge in the mentioned tools list may attend a technical evaluation for direct internship consideration. Would you like to be evaluated for this option?

Have you already completed any training in Data Science / Machine Learning / AI from another institute?

Options:

Yes

No

- Which of the following tools, technologies, or concepts are you familiar with?

(Select all that apply)

Advanced Python Programming

NumPy / Pandas for Data Analysis

Data Visualization (Matplotlib / Seaborn / Power BI / Tableau)

Machine Learning Algorithms (Regression, Classification, Clustering)

Supervised/UnSupervised

Reinforcement Learning with Practical

Deep Learning (CNN / RNN/Neural Networks)

Natuaral Language Processing

Generative AI / LLM Concepts

MLOps Concepts (Model Deployment / Monitoring)

Cloud Platforms for AI (AWS / Google Cloud / Azure)

Model Deployment using Flask / Django / APIs

Git / Version Control

I am a beginner and looking to learn these skills

- What challenges are you currently facing in building real projects or getting opportunities in Data Science?

This program includes a structured training phase with a fee, followed by practical internship exposure. Are you comfortable with this structure?
✔ Yes, I am comfortable

✔ I would like more details

✔ No, I am only looking for free opportunities

- What is your current level in Data Science / Programming?”

Options:

Beginner (I am starting from basics)

Intermediate (I have learned some concepts)

Advanced (I have worked on projects)

Work Location: In person

📌 Data Science Training & Internship Program (AI & Machine Learning) (India)
🏢 Singularis Software Technologies
📍 India