Data Science Training Course

Module 1: Python for Data Science

⏳ 2 weeks

• Topics: Python basics, data structures, libraries like NumPy and Pandas

• Hands-on: Perform exploratory data analysis and build Python-based data scripts

Module 2: Statistics & Probability

⏳ 2 weeks

• Topics: Descriptive stats, inferential stats, probability distributions

• Hands-on: Analyze datasets using statistical tests and confidence intervals

Module 3: Machine Learning with Scikit-learn

⏳ 3 weeks

• Topics: Supervised, unsupervised learning, model evaluation

• Hands-on: Build classification, regression, and clustering models

Module 4: Deep Learning with TensorFlow & Keras

⏳ 3 weeks

• Topics: Neural networks, CNNs, RNNs, activation functions

• Hands-on: Train and evaluate deep learning models on image/text data

Module 5: R Programming for Data Science

⏳ 2 weeks

• Topics: Data frames, dplyr, ggplot2, statistical modeling

• Hands-on: Perform data analysis and visualization using R

Module 6: SQL for Data Science

⏳ 1.5 weeks

• Topics: Joins, aggregations, subqueries, window functions

• Hands-on: Query structured data for analysis and reporting

Module 7: Data Visualization with Tableau & Power BI

⏳ 2 weeks

• Topics: Dashboards, filters, charts, calculated fields

• Hands-on: Build interactive business dashboards from raw data

Module 8: Big Data & Spark for Data Science

⏳ 2 weeks

• Topics: Hadoop ecosystem, Spark RDDs, Spark MLlib

• Hands-on: Process and analyze large datasets using PySpark

Module 9: Capstone Project

⏳ 2 weeks

• Topics: End-to-end data science case study involving real-world datasets

• Hands-on: Apply data science lifecycle: data wrangling, modeling, evaluation, visualization

Get certificate