pandas
Load, clean and reshape tabular data.
Machine Learning Fundamentals
- Explain supervised and unsupervised learning
- Train regression and classification models
- Certificate of completion when you finish every lesson
- Course languages
- English
- Certification
- Certificate of completion from InternHub
- Duration
- 9 weeks · Advanced level
Included with this course
8 topics
1 project
3 tools covered
Machine Learning Fundamentals certification
InternHub certificate of completion
Complete every topic of Machine Learning Fundamentals to get a certificate with your name and the course. Each certificate carries a unique number that employers can check on InternHub.
Why learn Data Science?
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Decisions run on data
Teams in every industry want people who can turn data into clear answers.
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Builds on skills you can reuse
Python, statistics and visualisation help in analyst, product and research roles.
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Learn by exploring real datasets
Each topic is practised on data, not just theory.
What placement assistance will you receive?
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Build your resume on InternHub
Add the course and your projects to your InternHub resume so recruiters see what you can do.
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Job alerts that match your skills
Turn on job alerts in your profile to hear about internships and fresher jobs that fit what you learn here.
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Apply from the same account
Apply to internships and jobs on InternHub with the profile you already have.
AI tools you will learn
Matplotlib
Plot charts that explain what the data shows.
Jupyter Notebook
Combine code, charts and notes in one place.
Machine Learning Fundamentals Curriculum
3 modules · 8 topics · 2h 42m total
Foundations
- What is machine learning?
- Train and test splits
Supervised learning
- Linear regression
- Logistic regression
- Decision trees
Evaluation and tuning
- Metrics that matter
- Cross-validation
- Clustering basics
Machine Learning Fundamentals project details
Sales data analysis
Capstone projectClean a sales dataset, find trends by month and region, and present the findings with charts.
Meet your instructor
Priya NairData scientist
Priya works on forecasting and analytics for retail companies and loves turning messy data into clear answers.
Machine Learning Fundamentals overview
A practical introduction to machine learning with scikit-learn. You will train, evaluate and improve models and learn to avoid common mistakes like overfitting.
What you will learn
- Explain supervised and unsupervised learning
- Train regression and classification models
- Evaluate models with the right metrics
- Tune models and avoid overfitting
Skills you will gain
Machine Learning
scikit-learn
Python
Model Evaluation
Prerequisites
- Python and pandas basics
- School-level maths
Machine Learning Fundamentals FAQs
Q. Do I need any prior experience?
Check the prerequisites above. Beginner courses start from the basics.
Q. How long do I have access to the course?
Once you enroll, the lessons stay available in My learning.
Q. Can I learn at my own pace?
Yes. Lessons are self-paced and your progress is saved as you mark them complete.
Q. Will I get a certificate?
Yes. When you complete every lesson you can open your certificate from the course page and print it. It has a number employers can verify on InternHub.
Q. Do I have to pay to enroll?
Online payment is not available yet. Enrolling gives you access to the lessons now and no payment is taken.