About This Course
This 14-week course is a deep dive into the end-to-end Data Science workflow using Python. You will go beyond basic analytics and learn to build and evaluate predictive models. The course covers the complete Data Science stack: data wrangling with Pandas, numerical computing with NumPy, visualization with Matplotlib and Seaborn, and machine learning with Scikit-learn. You will learn the theory and practical application of key ML algorithms for both regression and classification, feature engineering, and model evaluation, preparing you for a robust career in data science.
What You Will Learn
Key skills you will master in this Data Science course:
- Perform complex data manipulation and cleaning using Pandas and NumPy.
- Create insightful statistical visualizations with Matplotlib and Seaborn.
- Implement the complete machine learning workflow with Scikit-learn.
- Build and tune predictive models for regression and classification (e.g., Linear Regression, Random Forest).
- Evaluate model performance using metrics like accuracy, precision, recall, and R-squared.
Prerequisites
Basic understanding of Python programming (variables, functions, loops, data structures) is required. Familiarity with fundamental statistics (mean, median, standard deviation) is highly beneficial.
Target Audience
- Aspiring Data Scientists and Machine Learning Engineers.
- Data Analysts who want to move into predictive modeling.
- Software developers who want to specialize in data-driven applications.
Enroll in This Course
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Duration:14 weeks
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Level:Intermediate
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Mode:Online / Classroom
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Tracks:Normal/FastTrack
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Certificate:Yes
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Support:24/7 Mentorship
Need help? Call us at +1 (908) 428 7996.