Course Description
Dive deep into the world of data science with Python — the most in-demand programming language in the industry. This hands-on course takes you from absolute beginner to confident data practitioner through practical exercises, real datasets, and industry-relevant projects.
You’ll learn the entire data science pipeline — from data cleaning and analysis to visualization and machine learning — using Python and its powerful libraries like NumPy, Pandas, Matplotlib, Scikit-learn, and more. Whether you’re preparing for a data science role or looking to sharpen your skills, this A-to-Z learning journey equips you with everything you need.
Certification
Receive a verified certificate upon course completion. Showcase it on your LinkedIn profile, resume, or portfolio to highlight your Python and data science expertise to employers and clients.
Who This Course is for
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Beginners with no prior experience in data science or programming
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Aspiring data analysts, data scientists, or ML engineers
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Students and professionals transitioning into tech or analytics roles
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Python programmers who want to apply their skills in real-world data scenarios
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Anyone looking to learn data science through hands-on practice instead of just theory
What You’ll Learn
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Python essentials: data types, control flow, functions, and modules
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Working with data: NumPy for numerical computing, Pandas for data manipulation
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Data visualization with Matplotlib and Seaborn
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Exploratory Data Analysis (EDA) techniques
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Building and evaluating machine learning models using Scikit-learn
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Basic statistics and its applications in data science
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Real-world projects using publicly available datasets (e.g., Titanic, Iris, or customer sales data)
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Best practices for data cleaning, feature engineering, and model selection
Tools & Libraries Covered
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Python 3.x
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Jupyter Notebooks
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NumPy
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Pandas
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Matplotlib & Seaborn
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Scikit-learn
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Optional: Plotly, XGBoost, TensorFlow
