Machine Learning Internship Program
Machine Learning & AI Internship – Hands-on Industry Training
Machine Learning & AI Internship – Hands-on Industry Training
A project-based, industry-oriented training program designed to help students and professionals build strong foundations in Machine Learning and Artificial Intelligence. Focuses on Python for Data Science, supervised and unsupervised learning, model building, real-world dataset analysis, AI mini-projects, and deployment basics. Participants work with real datasets mirroring industry scenarios.
Course curriculum Empty
Basic programming knowledge (Python preferred)
Basic mathematics (statistics helpful)
Laptop with minimum 8GB RAM
Interest in AI & Data Science
Construct ML models from scratch using scikit-learn
Clean and preprocess real-world datasets
Evaluate and enhance model performance
Apply supervised & unsupervised ML algorithms confidently
Deploy ML models as REST APIs
Educational ERP Management, Student Information Systems (SIS), Data Analytics & Reporting, Django & Web Application Management, User Access & Role Management, NAAC & NBA Data Handling, Cloud & Database Management, UI/UX Optimization for Education Platforms, Automation & Workflow Design, Technical Support & System Monitoring
491.8
480 Students
18 Courses
600 Reviews
Skolr Platform Administrator & Education Technology Manager
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04 Feb, 2025
My Kaggle rank improved significantly after applying the feature engineering techniques taught here.
09 Nov, 2025
Real-world datasets for every project. Not Iris and Titanic — actual industry use cases.
21 Mar, 2026
Dr. Ananya's explanations of gradient descent and optimisation algorithms are the clearest I have found.
22 Feb, 2026
Real-world datasets for every project. Not Iris and Titanic — actual industry use cases.
05 Feb, 2026
The dataset preprocessing modules changed how I think about data. Clean data = better models, always.
28 Feb, 2026
Real-world datasets for every project. Not Iris and Titanic — actual industry use cases.
26 Mar, 2026
The dataset preprocessing modules changed how I think about data. Clean data = better models, always.
25 Feb, 2025
Dr. Ananya's explanations of gradient descent and optimisation algorithms are the clearest I have found.
19 Feb, 2025
Dr. Ananya's explanations of gradient descent and optimisation algorithms are the clearest I have found.
22 Jan, 2026
From Pandas to deploying a Scikit-learn model as a Flask API — this program takes you all the way.
24 Feb, 2026
Got my first data science internship after this program. The project portfolio was the deciding factor.
18 Mar, 2026
Real-world datasets for every project. Not Iris and Titanic — actual industry use cases.
16 Feb, 2025
The unsupervised learning modules on clustering and dimensionality reduction are gems.
28 Mar, 2025
Got my first data science internship after this program. The project portfolio was the deciding factor.
17 Mar, 2025
From Pandas to deploying a Scikit-learn model as a Flask API — this program takes you all the way.
11 Mar, 2025
From Pandas to deploying a Scikit-learn model as a Flask API — this program takes you all the way.
20 Jan, 2026
Got my first data science internship after this program. The project portfolio was the deciding factor.
30 Jun, 2025
From Pandas to deploying a Scikit-learn model as a Flask API — this program takes you all the way.
01 Feb, 2025
The dataset preprocessing modules changed how I think about data. Clean data = better models, always.
01 Mar, 2026
My Kaggle rank improved significantly after applying the feature engineering techniques taught here.
19 Mar, 2025
Dr. Ananya's explanations of gradient descent and optimisation algorithms are the clearest I have found.
08 Oct, 2025
The unsupervised learning modules on clustering and dimensionality reduction are gems.
27 Nov, 2025
The dataset preprocessing modules changed how I think about data. Clean data = better models, always.
14 Oct, 2025
Finally understood cross-validation, overfitting, and regularisation through the hands-on exercises.
06 Sep, 2025
From Pandas to deploying a Scikit-learn model as a Flask API — this program takes you all the way.
07 Aug, 2025
From Pandas to deploying a Scikit-learn model as a Flask API — this program takes you all the way.
08 Apr, 2025
From Pandas to deploying a Scikit-learn model as a Flask API — this program takes you all the way.
06 Feb, 2025
Got my first data science internship after this program. The project portfolio was the deciding factor.
16 Jan, 2025
The unsupervised learning modules on clustering and dimensionality reduction are gems.
14 Sep, 2025
My Kaggle rank improved significantly after applying the feature engineering techniques taught here.
25 Aug, 2025
Finally understood cross-validation, overfitting, and regularisation through the hands-on exercises.
08 Jan, 2025
My Kaggle rank improved significantly after applying the feature engineering techniques taught here.
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Students
38
language
English
Duration
00h 00mLevel
beginnerExpiry period
LifetimeCertificate
Yes
English
Certificate Course
38 Students
00h 00m