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Online Certified CourseData Science For Beginners
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Video-based Self-LearningLearn at your convenience
Subscription based 3 months validityAccess anytime, anywhere
Course Modules
Unit 01 Introduction Using Dataset
4 Videos
20 Assessments
Unit 02 Data Cleaning & Preprocessing
4 Videos
20 Assessments
Unit 03 Exploratory Data Analysis (eda)
4 Videos
20 Assessments
Unit 04 Basic Statistics For Data Science
4 Videos
20 Assessments
Unit 05 Data Visualization
4 Videos
20 Assessments
Unit 06 Python Libraries For Data Science
4 Videos
20 Assessments
Unit 07 Introduction To Machine Learning
2 Videos
10 Assessments
Unit 08 Applications Of Data Science
2 Videos
10 Assessments
Unit 09 Final Project
2 Videos
10 Assessments
Learning Objectives
- Understand different types of datasets and perform effective data exploration.
- Clean, preprocess, transform, and prepare data for analysis and modeling.
- Apply descriptive statistics and exploratory data analysis techniques to uncover insights.
- Create meaningful data visualizations and interpret charts effectively.
- Use NumPy and Pandas for data manipulation, analysis, and data handling.
- Understand the fundamentals of Machine Learning, including model training and evaluation.
- Apply data science techniques to solve real-world problems through case studies.
- Implement and present an end-to-end data science project using Python.
Why Enroll in This Course?
Improve academic performance
Boost confidence in communication
Enhance employability & growth
Build global English proficiency
Learn at your own pace
AICTE evaluated & trusted content
Why This Course Matters
- Builds a strong foundation in the complete data science lifecycle.
- Develops practical skills in data cleaning, preprocessing, and transformation.
- Strengthens analytical thinking through statistics and exploratory data analysis.
- Enhances the ability to communicate insights using effective data visualization.
- Provides hands-on experience with industry-standard Python libraries such as NumPy and Pandas.
- Introduces core Machine Learning concepts for predictive data analysis.
- Demonstrates how data science is applied across real-world domains through practical case studies.
- Develops project implementation, reporting, and presentation skills essential for data-driven careers.
The Best Investment in You
What You'll Learn in Each Module
NIPA offers high-quality online courses designed by experts to help you achieve your learning goals effectively.
Overview & Objectives
Data Science For Beginners
Structured online learning designed to help learners build practical speaking, presentation and interpersonal ability.
About This Course
This course introduces the complete Data Science workflow, covering dataset understanding, data cleaning and preprocessing, exploratory data analysis (EDA), basic statistics, data visualization, Python libraries (NumPy and Pandas), machine learning fundamentals, real-world applications, and project implementation. It equips learners with practical skills to collect, clean, analyze, visualize, and interpret data, apply statistical and machine learning techniques using Python, and develop data-driven solutions for real-world problems.
Meet Your Trainer
Hafsa Ihteshamuddin Ahmed
An Assistant Professor in Computer Science at Stanley College of Engineering and Technology for Women, Hyderabad, and a Ph.D. scholar at Jawaharlal Nehru Technological University, Hyderabad (JNTUH), specializing in AI in Healthcare. Experienced in teaching Machine Learning, Data Science, and Python Programming, with a strong focus on creating engaging, collaborative learning environments. Actively involved in research with publications in emerging areas such as Vision Transformers, Quantum Machine Learning, and AI-driven healthcare applications. Skilled in mentoring student projects and guiding innovative solutions in domains like computer vision, predictive analytics, and medical AI systems.
