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Data Science

Data Science

From data wrangling to predictive analytics and BI dashboards

14 Weeks Beginner to Intermediate Online / Project-based 5 modules

A practical, project-driven data science program covering Python, SQL, statistics, machine learning, and business intelligence tooling — with real datasets from BFSI, healthcare, and e-commerce.

Learning Outcomes

Build end-to-end ML pipelines
Create executive BI dashboards
Work with real datasets
Statistical modeling expertise

Full Syllabus

Click any module to expand the topic list.

Descriptive stats, distributions, hypothesis testing, and exploratory data analysis in Python.

Descriptive statistics & probability distributions
Hypothesis testing & p-values
Correlation & causation
Python EDA with Pandas & Seaborn

Cleaning messy real-world datasets and building publication-quality charts and dashboards.

Data cleaning: nulls, outliers, duplicates
Pandas advanced transformations
Matplotlib, Seaborn & Plotly
Dashboard building with Power BI & Tableau

Regression, classification, ensemble methods, and model selection on real business datasets.

Linear & logistic regression
Tree models & boosting (XGBoost, LightGBM)
Model evaluation & validation
Time series forecasting (ARIMA, Prophet)
Interpretable ML (SHAP, LIME)
Kaggle competition workflow

Advanced SQL, columnar query patterns, PySpark for large-scale data processing.

Advanced SQL: window functions, CTEs
Data warehouse concepts (star schema)
PySpark fundamentals
BigQuery & Databricks intro

Translating analysis into executive-ready presentations and interactive BI dashboards.

Data storytelling principles
Tableau advanced charts
Power BI DAX & report publishing
Capstone: end-to-end data science project

Certification Awarded

CyberNexus Certified Data Scientist (CCDS)

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Next batch starting soon. Limited seats available.

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Course At a Glance
  • Duration 14 Weeks
  • Level Beginner to Intermediate
  • Format Online / Project-based
  • Modules 5 modules
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