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What is the data analytics syllabus? - shruti - 19-06-2025
Below is an inclusive sample syllabus widely utilized in university or professional certification courses
(such as Google Data Analytics, Coursera, or university certificates):
Please visit our website:- Data Analytics Classes in Pune
Data Analytics Syllabus
Module 1: Introduction to Data Analytics
What is data analytics?
Role of a data analyst
Types of analytics: Descriptive, Diagnostic, Predictive, Prescriptive
Data-driven decision making
Module 2: Data Collection & Data Sources
Data types: Structured vs. unstructured
Data sources: Databases, APIs, web scraping, surveys
Data warehousing and data lakes
ETL (Extract, Transform, Load) processes introduction
Module 3: Data Cleaning & Preprocessing
Significance of clean data
Dealing with missing or inconsistent data
Data transformation and normalization
Tools: Excel, Python (Pandas), R
Module 4: Exploratory Data Analysis (EDA)
Descriptive statistics: Mean, median, mode, standard deviation
Data profiling
Discovery of trends and patterns
Visualization tools: Matplotlib, Seaborn, Tableau, Power BI
Module 5: Data Visualization & Communication
Best practices for visual storytelling
Visualizations: Bar charts, histograms, scatter plots, dashboards
Making reports and dashboards
Tools: Tableau, Power BI, Google Data Studio
Module 6: Statistical Analysis
Probability and distributions
Please visit our website:- Data Analytics Course in Pune
Hypothesis testing
Correlation vs. causation
Linear and logistic regression
Module 7: SQL for Data Analytics
Fundamentals of databases
SQL query writing
Joins, filters, and aggregations
Data manipulation and extraction
Basic syntax and data structures
Data analysis libraries (Pandas, NumPy, Matplotlib)
Reading, analyzing, and visualizing data
Introduction to scripting and automation
Module 9: Predictive Analytics (Advanced/Optional)
Introduction to machine learning
Supervised vs. unsupervised learning
Model building and evaluation
Algorithms: Decision trees, clustering, regression
Module 10: Data Ethics & Governance
Data privacy laws and compliance (e.g., GDPR)
Ethical use of data
Bias in data and algorithm
Capstone Project
Work on a real-world dataset
Perform full-cycle data analysis
Would you prefer a beginner version of this syllabus for business users, professionals, or data science professionals?
Please visit our website:- Data Analytics Training in Pune