Start with Python and data cleaning, then progress to statistics, visualizations, machine learning and a deployed beginner project. 1. Who can join Suitable for: College students, career switchers and beginners interested in data science Mandatory prerequisites: Basic computer literacy; no prior Python required 2. Duration 80 live hours • Approximately 14 weeks at 6 hours per week; actual timetable to be confirmed.
3. Mode Classroom - Thaiyur / Kelambakkam, OMR Chennai (subject to schedule) Live Online (subject to schedule)
4. Syllabus — five modules
Module 1: Python Programming & Data Manipulation with NumPy & Pandas Learning outcome: Write Python programs and manipulate datasets with NumPy and Pandas. Module 2: Exploratory Data Analysis (EDA) & Data Visualization (Matplotlib, Seaborn) Learning outcome: Clean data and communicate findings through charts. Module 3: Supervised Learning Algorithms: Regression, Classification & Decision Trees Learning outcome: Train and assess basic regression and classification models. Module 4:Unsupervised Learning: Clustering (K-Means, DBSCAN) & Dimensionality Reduction (PCA) Learning outcome: Apply clustering and dimensionality reduction to a sample dataset. Module 5: End-to-End ML Pipeline & Interactive Deployment using Streamlit Learning outcome: Package a machine-learning workflow into a Streamlit demonstration app. 5. Practical project Source capstone title: Predict Housing Market Prices with a Deployed Web Dashboard Student deliverable: A house-price prediction dashboard containing cleaned data, exploratory charts, trained regression model and an interactive Streamlit interface.
6. What is included Live trainer-led sessions Practical assignments Sample code or templates, as applicable Project feedback Learning assessment Perizona course-completion certificate subject to assessment 7. Upcoming batch Start date: To be announced. Students can register interest; dates are shared only after confirmation.
