Data Analyst/Data Science
Course Duration:50 Hours
What You Will Learn & Objectives
- Understand core concepts of Data Analytics & Data Science and how data is used for business decisions.
- Analyze and clean datasets using Excel, SQL, and Python for real-world scenarios.
- Master SQL to extract, filter, join, and manage large datasets from relational databases.
- Work with Python libraries like Pandas, NumPy, Matplotlib & Seaborn for analysis and visualization.
- Perform Exploratory Data Analysis (EDA) to identify patterns, correlations, and insights.
- Learn essential Statistics & Probability for analytical decision-making and A/B testing.
- Build interactive dashboards using Power BI or Tableau for business reporting.
- Apply Machine Learning basics (Regression, Classification, Clustering) on real datasets.
- Create end-to-end data projects including data cleaning → analysis → visualization → ML modeling.
- Develop industry-ready portfolios with multiple projects and prepare for Data Analyst/Data Science interviews.
About Course
This course equips learners with end-to-end skills required to collect, clean, analyze, visualize, and model data to solve real business problems. Students will work on practical datasets, create dashboards, build predictive models, and learn how to communicate insights clearly to stakeholders.
Course Curriculum
Data Analytics Foundations (The Core Layer)
- Introduction to Data Analytics & Data Science: Data roles, workflows, industry use-cases.
- Data Types & Structures: Structured vs unstructured data, files, rows, columns.
Data Collection Process: APIs, databases, CSV/Excel importing.
Excel & Spreadsheet Mastery
SQL for Data Analysis (RDBMS)
Python for Data Analytics
Data Cleaning & Preprocessing
Exploratory Data Analysis (EDA)
Statistics & Probability (For Data Science)
Data Visualization (BI Tools + Python)
Machine Learning – Supervised Learning
Machine Learning – Unsupervised Learning
Big Data & Cloud Analytics (Overview)
Business Intelligence & Reporting
Capstone Projects & Integration
Requirements
- Basic understanding of computer operations.
- No prior coding or analytics experience required (Beginner to Advanced).
- A laptop with at least 8GB RAM (recommended 16GB for machine learning workloads).
- Stable internet connection for accessing datasets, dashboards, and cloud tools.
- Basic English communication skills for understanding analytics terminology.
Material Includes
- Source Code & Notebooks for all Python, SQL, and Machine Learning projects.
- Data Analytics & Data Science Cheat Sheets (Python, Pandas, NumPy, Statistics, SQL).
- Practice Datasets (Finance, HR, E-commerce, Healthcare, Marketing, Sales).
- E-books on Data Analytics, BI Dashboards, and Machine Learning.
- Access to our Exclusive Data Analyst Community (Doubt-solving + Career guidance).
- Capstone Project Templates for GitHub portfolio building.
- Power BI & Tableau Practice Files for visualization training.
₹200
₹600 Discount 83% off
Benefits Obtained :
- Webinar Link
- Training Evaluation Test
- Completion Certification
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