Data Science
Discover the Power of Data Science: Transform Your Career and Elevate Your Skills
In today's digital age, data is the new gold, and mastering the art of data science is your key to unlocking unlimited career opportunities. Whether you're an aspiring data scientist, a seasoned professional looking to upskill, or someone eager to break into the tech industry, our Comprehensive Data Science Course is designed to equip you with the knowledge and tools you need to thrive in this data-driven world.
- Description
- Curriculum
- Reviews
Course Highlights
📊 Comprehensive Curriculum
- Data Exploration and Visualization: Learn to uncover insights and communicate findings effectively.
- Statistical Analysis: Master the principles of probability, hypothesis testing, and statistical modeling.
- Machine Learning: Dive into algorithms like regression, classification, clustering, and deep learning.
- Big Data Technologies: Get hands-on with tools like Hadoop, Spark, and cloud platforms.
🛠️ Practical Tools and Techniques
- Programming with Python and R: Write efficient code for data analysis and model building.
- SQL for Data Management: Manage and query large datasets with ease.
- Data Visualization: Create compelling visualizations using Tableau and Matplotlib.
📚 Real-World Projects
- E-commerce Analysis: Analyze customer behavior and build recommendation systems.
- Healthcare Analytics: Predict patient outcomes and optimize healthcare processes.
- Finance and Risk Management: Develop models for credit scoring and fraud detection.
🎓 Certification and Recognition
- Industry-Recognized Certification: Earn a certificate that showcases your expertise and boosts your resume.
- Portfolio Development: Build a portfolio of projects that demonstrates your skills to potential employers.
COURSE CURRICULUM
COURSE OVERVIEW
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2
OVERVIEW OF MODULE :1 INTRODUCTION TO DATA SCIENCE -
3
OVERVIEW OF MODULE : 2 (Data Wrangling and Preprocessing )
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4
OVERVIEW OF MODULE :3 (Exploratory Data Analysis (EDA) )
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5
OVERVIEW OF MODULE - 4(Statistical Analysis and Hypothesis Testing)
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6
OVERVIEW OF MODULE : 5 ( Machine Learning Basics)
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7
OVERVIEW OF MODULE : 6 ( Model Evaluation and Validation )
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8
OVERVIEW OF MODULE : 07 ( Data Science Project)
Introduction to Data Science
Data Wrangling and Preprocessing
Exploratory Data Analysis (EDA)
Statistical Analysis and Hypothesis Testing
Machine Learning Basics
Model Evaluation and Validation
Data Science Project
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