10 Sections
40 Lessons
Lifetime
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Module 1: Introduction to Data Science
Understand the fundamentals of data science, lifecycle, and real-world applications across industries.
4
1.1
Tools Overview
1.2
Industry Use Cases
1.3
Data Science Lifecycle
1.4
What is Data Science?
Module 2: Python for Data Science
Learn Python programming required for data science including data structures and libraries.
4
2.1
Python Basics
2.2
Data Types & Functions
2.3
NumPy & Pandas
2.4
Data Handling
Module 3: Data Analysis & Visualization
Learn how to analyze and visualize data to extract meaningful insights using Python libraries.
4
3.1
Data Cleaning
3.2
Exploratory Data Analysis (EDA)
3.3
Matplotlib & Seaborn
3.4
Data Visualization
Module 4: Statistics & Probability
Understand statistical concepts required for data analysis and machine learning.
4
4.1
Descriptive Statistics
4.2
Probability Basics
4.3
Probability Basics
4.4
Hypothesis Testing
Module 5: SQL & Data Handling
Learn SQL to manage and query structured data efficiently.
4
5.1
SQL Basics
5.2
Queries & Joins
5.3
Data Extraction
5.4
Database Concepts
Module 6: Machine Learning
Learn machine learning algorithms for prediction and data modeling.
4
6.1
Supervised Learning
6.2
Unsupervised Learning
6.3
Regression
6.4
Classification
Module 7: Model Evaluation & Optimization
Understand how to evaluate and improve machine learning model performance.
4
7.1
Model Evaluation Metrics
7.2
Cross Validation
7.3
Hyperparameter Tuning
7.4
Overfitting & Underfitting
Module 8: Real-Time Projects
Work on real-world datasets and build predictive models for practical applications.
4
8.1
Data Analysis Project
8.2
Predictive Modeling
8.3
Business Case Studies
8.4
Data Insights
Module 9: Data Visualization Tools
Learn advanced visualization techniques to present data insights effectively.
4
9.1
Dashboards
9.2
Data Storytelling
9.3
Visualization Best Practices
9.4
Reporting
Module 10: Case Studies & Deployment Basics
Understand how data science is applied in real industries and learn basics of deployment.
4
10.1
Industry Case Studies
10.2
Business Applications
10.3
Model Deployment Basics
10.4
Best Practices
Data Science Training in Hyderabad & Online | Job-Oriented Program with Real-Time Projects
Curriculum
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