Python for Data Science
Master Python Programming for Data Analysis, Visualization, and Machine Learning
Syed Nasrullah
Intermediate
Data Science
Course Overview
Python for Data Science is a practical, project-based course designed to teach Python programming specifically for Data Science applications. Starting with Python fundamentals, learners progress to data manipulation, cleaning, preprocessing, exploratory data analysis (EDA), and visualization using industry-standard tools such as NumPy, Pandas, Matplotlib, and Seaborn. Students will learn how to import, transform, analyze, and visualize real-world datasets while following best coding practices. Every topic is supported with coding demonstrations, hands-on exercises, quizzes, assignments, and mini projects that reinforce practical learning. The course prepares students to work confidently with structured data and build a strong foundation for Machine Learning, Artificial Intelligence, and Data Analytics. Whether you are a beginner, student, software developer, or working professional, this course provides the essential Python skills required for modern Data Science careers.
This course is designed for guided live learning. You will move through concepts, Tutor-led demonstrations, practice tasks, review sessions, assignments and a final project that proves your understanding.
Learning Outcomes
- Understand Python fundamentals for Data Science
- Work with NumPy for numerical computing
- Analyze data using Pandas
- Clean and preprocess datasets
- Perform Exploratory Data Analysis (EDA)
- Create professional data visualizations
- Work with CSV and Excel datasets
- Apply descriptive statistics using Python
- Manipulate and transform real-world data
- Handle missing values and outliers
- Prepare datasets for Machine Learning
- Develop practical data analysis projects
Requirements
- Basic computer knowledge
- No prior programming experience required
- Laptop or Desktop (Windows, Linux or macOS)
- Python installed
- Jupyter Notebook or VS Code
- Willingness to practice coding
Who This Course Is For
- Students
- Beginners in Data Science
- Python Developers
- Data Analysts
- Business Analysts
- Machine Learning Beginners
- Working Professionals
- Researchers
- Anyone interested in Data Science
Assignments
Assignments help the Tutor check your progress and give completion feedback. After purchase, assigned work also appears inside the student dashboard.
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 2 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 4 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 6 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 6 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 2 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 5 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 5 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 5 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 2 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 4 Hours
Practice the topic, submit your notes or project work and receive Tutor feedback before moving ahead.
Suggested time 5 Hours
Tutor Details
Syed Nasrullah
Data Science Tutor
Live Tutor focused on practical Data Science course outcomes, guided projects and clear student feedback.
Message to Tutor - Syed Nasrullah
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