Description
Curriculum
Instructor
The Data Science course provides in-depth knowledge of data analysis, machine learning, and statistical modeling. You’ll learn essential tools and technologies like Python, R, SQL, Tableau, and TensorFlow. The course focuses on practical applications through real-world projects, preparing you for roles such as Data Scientist, Data Analyst, and Machine Learning Engineer.
- 7 Sections
- 0 Lessons
- 32 Weeks
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- Python ProgrammingAdvanced Python techniques and debugging. Libraries: NumPy, Pandas, Matplotlib, Seaborn for data manipulation and visualization.0
- Statistics and ProbabilityProbability distributions, Bayes Theorem, and statistical significance. Hypothesis Testing (ANOVA, Chi-Square Test).0
- Machine LearningSupervised Learning (Linear Regression, Decision Trees, Random Forest). Unsupervised Learning (Clustering, Dimensionality Reduction with PCA). Model Evaluation (Confusion Matrix, ROC Curve).0
- Deep LearningConvolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Frameworks: TensorFlow and Keras.0
- Data VisualizationDashboards using Tableau and Power BI.0
- Big DataIntroduction to Spark and Hadoop for large-scale data processing.0
- Capstone ProjectPredictive modeling for real-world datasets such as customer churn or sales forecasting.0
0 Students20 Courses
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