Data Science Course
Learn Data Science from fundamentals to practical applications with Python, SQL, statistics, data analysis, machine learning, data visualization, and real-world datasets.
Data Science Beginner to Job-ReadyData Science
Learn Data Science from fundamentals to practical applications with Python, SQL, statistics, data analysis, machine learning, data visualization, and real-world datasets.
- Hands-On Data Science Projects
- Practical Industry-Oriented Curriculum
- Python
Course Overview
Build skills that go beyond theory
Data Science course in Agra at AI Scholars is designed for suitable for beginners, students, graduates, job seekers, and working professionals interested in data science and analytics. who want structured, mentor-led training with practical work, certification guidance, and career preparation.
Build practical Data Science skills through hands-on training in Python, SQL, statistics, data analysis, machine learning, and data visualization. Learn to work with real-world datasets, extract meaningful insights, build predictive models, and create data-driven solutions through practical projects.
Learning Outcomes
What you will be able to build
Turn guided lessons into practical abilities you can explain clearly in projects, internships, and interviews.
Analyze and clean real-world datasets
Practice this through guided work using Python, NumPy, Pandas and course projects.
Use Python and SQL for data analysis
Practice this through guided work using Python, NumPy, Pandas and course projects.
Apply statistics to solve data-driven problems
Practice this through guided work using Python, NumPy, Pandas and course projects.
Create meaningful data visualizations and dashboards
Practice this through guided work using Python, NumPy, Pandas and course projects.
Build and evaluate machine learning models
Practice this through guided work using Python, NumPy, Pandas and course projects.
Apply supervised and unsupervised learning techniques
Practice this through guided work using Python, NumPy, Pandas and course projects.
Extract actionable insights from business data
Practice this through guided work using Python, NumPy, Pandas and course projects.
Build portfolio-ready Data Science projects
Practice this through guided work using Python, NumPy, Pandas and course projects.
Course Curriculum
A clear path from foundations to final project work
Modules are structured from the available course curriculum, keeping the learning sequence easy to scan without changing the underlying course data.
- Python Programming for Data Science
- Statistics & Probability
- Data Collection & Cleaning
- Exploratory Data Analysis (EDA)
- Data Visualization
- Machine Learning Fundamentals
- Supervised & Unsupervised Learning
- Feature Engineering
- Model Evaluation & Optimization
- Deep Learning Basics
- Natural Language Processing (NLP)
- Capstone Projects
Tools & Technologies
Learn the tools used in modern workflows
The Data Science learning path includes practical exposure to the technologies listed in the course curriculum.
Live Project Experience
Build projects you can actually show in interviews
Transform what you learn into portfolio-ready work, documented demos, and practical explanations for professional conversations.
Portfolio Application
Hands-On Data Science Projects
Dashboard Workflow
Practical Industry-Oriented Curriculum
API or Automation Project
Python
Final Project Demo
SQL & Machine Learning Training
Career Outcomes
Turn your skills into career-ready proof
The program connects classroom learning with project review, portfolio development, interview communication, and course counseling.
Industry-Relevant Skills
Understand how modern teams apply technical skills in practical workflows and project decisions.
Mentor Reviews
Receive guidance on project clarity, presentation quality, and gaps to improve before interviews.
Portfolio Proof
Use projects, demos, documentation, and explanations to demonstrate what you can build.
Interview Preparation
Practice explaining your project choices, tools, problem-solving process, and learning path.
Placement Roadmap
From learning to interviews
A simple progression helps students move from fundamentals to project confidence and career conversations.
Skill Foundation
Build strong technical fundamentals through guided training.
Guided Projects
Apply skills through real-world project work.
Portfolio Polish
Organize your strongest work into an interview-ready portfolio.
Mock Interviews
Practice technical explanations and professional communication.
Career Counseling
Receive guidance for internships, job profiles, and next career steps.
Mentor-Led Learning
Learn with guidance, feedback, and real project reviews
AI Scholars mentors help learners connect concepts with practical execution through live training, project checkpoints, portfolio improvement, and interview preparation.
Course Inquiry
Get batch timings, fee details, and demo class guidance
Share your details and the AI Scholars team will contact you about Data Science, curriculum, certification, and admission next steps.
Data Science
Request a callback for course counseling.
FAQ
Questions before joining Data Science?
A few quick answers before you speak with the counseling team.
Yes. The program starts with fundamentals and moves toward practical projects, portfolio work, and interview readiness.
Internship guidance is available with project tracks, mentor reviews, and certification options where applicable.
Yes. Project work is part of the learning path so students can demonstrate practical skills, not just complete theory.
AI Scholars supports resume improvement, mock interviews, portfolio review, and career counseling.
Helpful Next Pages
Explore connected programs and guides
Useful internal resources for students comparing programs, services, and local training options.
Start Your Learning Journey
Build practical skills with AI Scholars
Speak with our team about batches, curriculum, demo classes, certification, and career guidance.