Data Science | Techyversity

Course preview

About This Course

A complete Data Science and AI/ML program covering feature engineering, foundational mathematics, supervised and unsupervised machine learning, deep learning, NLP, computer vision, time series and generative AI. This course is designed to take learners into advanced, industry-ready data science and AI skills.

Throughout the program, students learn by working with real datasets, training ML and DL models, building NLP pipelines, exploring computer vision techniques, and creating deployable AI applications. Every concept is explained simply, supported by mathematical intuition, and practiced through hands-on projects to ensure students build strong practical skills used in modern data science roles.

Learners begin with ML foundations and feature engineering, then progress step-by-step into regression and classification models, clustering, neural networks, transformers, and generative AI workflows. By the end of the program, students complete multiple portfolio-ready AI and ML projects, gain confidence with advanced modeling, and prepare for Data Scientist, ML Engineer, or AI Developer positions.

What You'll Learn

Understand ML foundations & core concepts

Apply feature engineering techniques to prepare data

Mathmematics for Data Science and AI/ML

Build supervised ML models (regression & classification)

Work with unsupervised learning & clustering algorithms

Use Scikit-learn for end-to-end ML workflows

Build deep learning models with TensorFlow/PyTorch

Apply NLP techniques including embeddings & transformers

Work with computer vision using CNNs

Develop Time Series Applications

Develop generative AI & LLM-based applications

Fine-tune AI models and work with API-based LLMs

Deploy ML/DL models using Streamlit & Hugging Face

Build a job-ready data science and AI portfolio

Requirements

Python, NumPy, Matplotlib & Seaborn (Prerequisite)
Laptop or desktop
Stable internet connection
Willingness to practice 4-6 hours/week

Who This Course Is For

IT students with Python knowledge
Data Analysts expanding into ML & AI
Career switchers entering data science or ML engineering
Fresh graduates interested in AI technologies
Junior analysts growing toward data science roles
Aspiring data scientists & AI developers