Applied Data Analytics with Python and SQL
This course is part of Applied Data Analytics.
This comprehensive course equips learners with practical skills in data analytics using Python and SQL. Designed for beginners and data enthusiasts, it provides a thorough foundation in Python programming concepts while exploring powerful libraries like NumPy and Pandas for efficient data manipulation and analysis. Students will learn to create impactful visualizations using Matplotlib, Seaborn, and Plotly, while also gaining expertise in SQL for database management and querying. The curriculum includes web scraping techniques to gather data from various online sources, establishing a complete toolkit for modern data analysis. Through hands-on projects and practical exercises, participants will develop the ability to extract meaningful insights from real-world datasets and apply data-driven solutions across industries.
Instructors:
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What you'll learn
Write effective Python programs using variables, data types, and control flow structures
Manipulate and analyze large datasets using NumPy and Pandas libraries efficiently
Create insightful data visualizations with Matplotlib, Seaborn, and Plotly for reporting
Execute SQL queries to manage and analyze relational database data accurately
Implement web scraping techniques to collect data from online sources
Combine Python and SQL for comprehensive data analysis workflows
Skills you'll gain
This course includes:
7.3 Hours PreRecorded video
15 assignments
Access on Mobile, Tablet, Desktop
Batch access
Shareable certificate
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Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 4 modules in this course
This course provides a comprehensive introduction to data analytics using Python and SQL, designed for beginners and data enthusiasts alike. The curriculum begins with Python fundamentals, covering essential programming concepts like data types, control flow, and functions. Students then progress to data manipulation and analysis using NumPy and Pandas, learning to efficiently handle large datasets. The visualization component explores creating impactful charts and graphs with Matplotlib, Seaborn, and Plotly. The course also covers web scraping techniques for data collection and SQL database operations, including normalization principles and practical queries. Throughout the program, hands-on assignments reinforce learning concepts, culminating in a practical project analyzing police records data.
Python Essentials
Module 1 · 5 Hours to complete
Exploring Data with NumPy and Pandas
Module 2 · 3 Hours to complete
Web Scraping and SQL
Module 3 · 3 Hours to complete
Course Wrap-Up and Assessment
Module 4 · 1 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Applied Data Analytics
Instructor
Inspiring the Next Generation of Tech Professionals
Edureka is dedicated to providing high-quality, instructor-led online training, empowering professionals to enhance their skills in various domains. The platform features a diverse team of experienced instructors who are passionate about teaching and possess extensive industry knowledge. These instructors facilitate a wide range of courses covering topics such as data science, artificial intelligence, machine learning, and cloud computing. Edureka's commitment to education is reflected in its innovative approach to learning, which includes interactive sessions, real-world projects, and 24/7 support for students. By fostering a collaborative learning environment, Edureka ensures that learners not only acquire technical skills but also develop critical thinking and problem-solving abilities essential for success in today's fast-paced job market.
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Frequently asked questions
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