Description
📜 Description:
This Basic to Advanced Data Science with AI course is designed to take you from zero knowledge to professional-level data science skills. You’ll learn the mathematics, programming, statistics, data analytics, and machine learning techniques required to solve real-world business and AI problems.
The course starts with core mathematical foundations like linear algebra, calculus, probability, and statistics, then progresses to Python programming and data preprocessing techniques. From there, you’ll master exploratory data analysis, machine learning algorithms (regression, classification, clustering, time-series forecasting), and model optimization methods.
By the end, you’ll be able to analyze, visualize, and model data using industry-standard tools like NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, SQL, and Tableau.
✅ What You Will Learn
📐 Mathematics & Statistics for Data Science
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Linear Algebra & Calculus Essentials
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Probability Theory & Distributions
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Descriptive & Inferential Statistics
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Hypothesis Testing & Statistical Tests
💻 Python Programming for Data Science
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Core Python Programming Concepts
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Data Science Libraries: NumPy, Pandas, Matplotlib, Seaborn, SciPy
🧹 Data Preprocessing & Preparation
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Data Cleaning & Wrangling
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Feature Engineering & Feature Selection
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Dimension Reduction (PCA)
📊 Data Analytics
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Exploratory Data Analysis (EDA) Techniques
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Visualization & Insight Extraction
🤖 Machine Learning (ML)
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Regression: Linear, Polynomial, Lasso, Ridge, Elastic Net
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Classification: KNN, Logistic Regression, SVM, Naive Bayes, Decision Tree, Random Forest, AdaBoost, Gradient Boost, XGBoost
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Clustering: K-Means, Hierarchical, DBSCAN
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Time Series Forecasting: AR, ARMA, ARIMA
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Additional ML Techniques: PCA, Recommendation Systems, Association Rules
⚙ Model Selection & Optimization
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Overfitting & Underfitting (Bias-Variance Tradeoff)
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Cross-Validation & Hyperparameter Tuning
📑 Data Science Tools
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SQL for Data Queries
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Tableau for Data Visualization
👤 Who Is This Course For?
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Beginners aiming to start a career in Data Science
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Analysts & Engineers looking to add AI & ML skills
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Students & Researchers working on data-driven projects
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Professionals preparing for Data Science job interviews

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