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Artificial Intelligence & Machine Learning Intern

IG Tech

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Original Job Summary

About the Role

The Artificial Intelligence & Machine Learning Intern role at IG Tech offers a hands-on, project-driven virtual internship designed for students and fresh graduates. This internship provides practical exposure to data science, machine learning algorithms, and AI applications.

Internship Overview

As an AI & ML Intern, you will explore data preprocessing, model building, and AI-driven solutions using real-world datasets. This experience prepares you for the entire machine learning workflow.

Qualifications

  • Pursuing or completed a degree in Computer Science, Data Science, AI/ML, or related fields
  • Knowledge of Python and libraries like NumPy, Pandas, Matplotlib
  • Familiarity with machine learning frameworks such as Scikit-learn, TensorFlow, and PyTorch
  • Understanding of data preprocessing and model evaluation
  • Strong analytical and logical thinking

What You’ll Gain

  • Practical experience in AI & ML projects
  • Internship Certificate and Letter of Recommendation
  • Opportunity to work on real-world datasets

Key skills/competency

  • Artificial Intelligence
  • Machine Learning
  • Data Science
  • Python
  • NumPy
  • Pandas
  • TensorFlow
  • PyTorch
  • Model Building
  • Data Preprocessing

How to Get Hired at IG Tech

🎯 Tips for Getting Hired

  • Customize your resume: Highlight AI, ML, and Python skills.
  • Research IG Tech: Understand their virtual internship approach.
  • Tailor your cover letter: Emphasize project experience and analytical skills.
  • Prepare for technical interviews: Review machine learning frameworks and code samples.

📝 Interview Preparation Advice

Technical Preparation

Review Python basics and data libraries.
Practice machine learning model building exercises.
Study TensorFlow, PyTorch nuances.
Solve real-world data preprocessing problems.

Behavioral Questions

Describe a challenging project you handled.
Explain teamwork in remote settings.
Discuss handling deadlines under pressure.
Share learning experiences from past projects.