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Data Analytics

Master data analytics—from Python fundamentals and NumPy/Pandas to statistical thinking, machine learning, and Power BI. Industry-aligned curriculum from SKILLUMNI for data-driven insights.

1,500+ Students
4.8
Beginner to Advanced

What You'll Learn

  • Python internals, Jupyter Notebook, data structures, and file I/O
  • NumPy and Pandas for data manipulation and analysis
  • Data visualization with Matplotlib and Seaborn
  • Statistical thinking, linear & logistic regression, and model evaluation
  • Data preprocessing, decision trees, random forest, and neural networks
  • Power BI dashboards, DAX, ETL pipelines, and AI-powered reporting

About This Course

This Data Analytics course covers the full journey from Python fundamentals to advanced analytics and machine learning. You will learn Python architecture, data structures, file handling, loops and conditionals, and hands-on skills with Jupyter Notebook and Anaconda.

Progress through NumPy and Pandas, exploratory data visualization, statistical thinking, supervised and unsupervised learning, linear and logistic regression, data preprocessing, tree-based models, and neural network fundamentals. The course concludes with Power BI for ETL pipelines, DAX calculations, reports, dashboards, and AI-powered analytics.

Course Benefits

  • 35+ hrs of Training
  • Industry-based assessments
  • Outcome-based learning
  • Hands-on projects
  • Lifetime LMS Access
  • Industry certification

Course Curriculum

1. Python Internals, Architecture & Data Structure

  • • Installation of Anaconda Prompt
  • • Jupyter Notebook – An Overview
  • • Shortcut Keys in Jupyter Notebook
  • • Data Types in Python

2. Python Reading & Writing Files in Python

  • • Rules for Naming the Variables
  • • List, Tuple, Set, Dictionary
  • • Introduction to Files and Directories
  • • Introduction to the Command Prompt or Terminal Paths
  • • Text Files: Reading from a Text File (using with)

3. Loops and Conditionals in Python

  • • If, Elif, and Else Conditions
  • • For and While Loops

4. Data Analysis & Manipulation with NumPy

  • • Machine Learning Libraries
  • • NumPy – Hands-on

5. Pandas: Python Data Science Package

  • • Pandas – Hands-on

6. Exploratory Data Visualization in Python with Matplotlib

  • • Exploring & Extracting Insights from Data
  • • Data Visualization Basics
  • • Matplotlib – Hands-on
  • • Seaborn – Hands-on

7. Statistical Thinking in Python (Part 1)

  • • Thinking Statistically – Introduction
  • • Measures of Central Tendency
  • • Measures of Dispersion
  • • IQR Statistics – Hands-On

8. Supervised Learning & Un-Supervised Learning

  • • Classification vs Regression
  • • Supervised vs Unsupervised Learning
  • • Linear Regression – Hands-on
  • • Metrics in Linear Regression – Hands-on
  • • Fine-Tuning Your Model

9. Logistic Regression

  • • Introduction to Logistic Regression
  • • Hands-on with Logistic Regression
  • • Metrics in Logistic Regression

10. Linear Regression

  • • Introduction to Linear Regression
  • • Hands-On with Linear Regression using Python
  • • Metrics in Linear Regression

11. Pre-processing for Machine Learning in Python

  • • Introduction to Data Preprocessing
  • • Exploratory Data Analysis (EDA)
  • • Missing Values
  • • Outliers
  • • Standardizing Data / Scaling Techniques
  • • Feature Scaling and Feature Selection

12. Tree Based Models: Classification and Regression Tree

  • • Decision Tree
  • • Boosting Random Forest
  • • Bagging

13. Fundamentals of Neural Network

  • • Neural Network

14. Power BI

  • • Introduction to Power BI Desktop
  • • ETL Pipeline in Power BI
  • • Calculating Fields with DAX
  • • Visualising Data with Reports
  • • AI Functionalities of Power BI

Requirements

  • Basic numeracy and interest in data-driven decisions
  • No prior analytics experience required; beginners welcome
  • Computer with internet connection
  • Willingness to learn Python, NumPy, Pandas, Matplotlib, and Power BI

Material Includes

  • 35+ Hours of Video Lectures
  • Lifetime LMS Access
  • Section Quizzes & Assessments
  • Industry-Based Hands-on Projects
  • Certificate of Completion

Why Choose This Course

Industry-Aligned Curriculum

Structured curriculum from Python fundamentals to machine learning, visualization, and Power BI

Hands-On Projects

Build dashboards, run predictive models, and analyze real-world datasets

Industry Certification

Earn a recognized certificate for roles in data analytics, BI, and data science

Mentor Support

Get guidance from experts in data analytics and machine learning

Live Sessions & LMS Access

Attend scheduled live sessions with lifetime access to course materials and recordings

Career Support

Access placement assistance and connect with professionals in analytics and BI

Ready to Master Data Analytics?

Join students learning Python, NumPy, Pandas, statistics, machine learning, and Power BI. Start your journey in data analytics today.

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