Data Science Internship
About This Course
A structured virtual internship covering 6 weeks of
curriculum — from Python basics to deploying production
ML models. Your access duration depends on your chosen
tier (15 days to 6 months).
Includes:
– 24 animated concept lessons
– 24 deep-dive theory sessions
– 24 IDE-style practice labs
– Weekly live mentor sessions (Core tier and above)
– 2 industry projects + 1 real-world capstone
– Career module — resume, GitHub portfolio, interview prep
Outcome: You will leave with GitHub-ready projects,
an ATS-friendly resume, a working ML pipeline you built
yourself, and a verified internship certificate.
Mentor: Synkoc Industry Expert
Expertise: Data Science · Python · ML · DL · NLP ·
GenAI · AWS/GCP/Azure · MLOps
Learning Objectives
Write Python code to load, clean and analyse real datasets
Build and evaluate ML models — Linear Regression, Logistic Regression, Decision Trees, Random Forests
Perform Exploratory Data Analysis (EDA) on real Indian business datasets
Apply feature engineering and hyperparameter tuning to improve model accuracy
Implement K-Means clustering and PCA for unsupervised learning
Build and train your first neural network end-to-end
Complete a Customer Churn Prediction project from scratch
Write an ATS-friendly Data Science resume
Build a professional GitHub portfolio
Answer ML interview questions confidently
Material Includes
- 24 Animated concept lessons
- 24 Deep-dive theory sessions
- 24 IDE-style practice labs
- Weekly live mentor sessions (Core tier and above)
- Career module — resume writing, GitHub portfolio, interview prep
- Reference guide PDF for your domain
- Discord community access
Requirements
- Basic computer skills — no prior coding experience needed
- A laptop or desktop with internet connection
- Google account for Google Colab (free, no installation required)
- Willingness to commit 1-2 hours daily to the program
- A genuine interest in Data Science and Machine Learning
Target Audience
- Final-year B.Tech, BCA, B.Sc, MCA, or MBA students preparing for campus placements
- Freshers and recent graduates looking to build a Data Science portfolio
- Working professionals from non-tech backgrounds switching careers into Data Science
- Anyone who wants a structured, mentor-guided introduction to Python and Machine Learning
- Students applying for Data Science internships at Indian startups and MNCs
Curriculum
72 Lessons40h
Week 1 — Python & Data Wrangling
Build your foundation: Python, NumPy, pandas, and data cleaning. By end of this week you can read any messy CSV and turn it into clean, analyzable data.
Lesson 1 — Python Basics for Data Science (Animated)
Lesson 1 — Python Basics for Data Science (Theory)
Lesson 1 — Python Basics for Data Science (Lab)
Lesson 2 — NumPy for Numerical Computing (Animated)
Lesson 2 — NumPy for Numerical Computing (Theory)
Lesson 2 — NumPy for Numerical Computing (Lab)
Lesson 3 — pandas for Data Manipulation (Animated)
Lesson 3 — pandas for Data Manipulation (Theory)
Lesson 3 — pandas for Data Manipulation (Lab)
Lesson 4 — Data Cleaning & Preparation (Animated)
Lesson 4 — Data Cleaning & Preparation (Theory)
Lesson 4 — Data Cleaning & Preparation (Lab)
Week 2 — Statistics & Exploratory Data Analysis
Think like a scientist: descriptive stats, visualisations, hypothesis testing, and the EDA checklist that every senior data scientist runs on every new dataset.
Week 3 — Supervised ML I
Train your first ML models from scratch. The workflow, train/test split, Linear Regression, Logistic Regression, and Decision Trees with real Indian datasets.
Week 4 — Supervised ML II
Make your models production-grade: Random Forests, feature engineering, regularisation, and hyperparameter tuning. From 75% accuracy to 88%.
Week 5 — Unsupervised & Deep Learning
Expand the toolkit: customer segmentation with K-Means, dimensionality reduction with PCA, and your first neural network for end-to-end ML pipelines.
Week 6 — Capstone Project
Build a complete Customer Churn ML system end-to-end: EDA, baseline, model, evaluation, deployment, and explainability. Your portfolio centrepiece.
Bonus — Career Awareness
Turn the internship into job offers: ATS-friendly resume, polished GitHub portfolio, and ML interview prep covering bias/variance, metrics, and STAR answers.
Earn a certificate
Add this certificate to your resume to demonstrate your skills & increase your chances of getting noticed.
Free
Material Includes
- 24 Animated concept lessons
- 24 Deep-dive theory sessions
- 24 IDE-style practice labs
- Weekly live mentor sessions (Core tier and above)
- Career module — resume writing, GitHub portfolio, interview prep
- Reference guide PDF for your domain
- Discord community access
Free
