Uploaded August 2026 | Updated September 2026, 2 weeks ago

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In this video, Python and SQL for Data Analytics Full Course 2026, you’ll learn how to use Python and SQL together to extract, clean, analyze, and visualize data like a professional data analyst. This complete course takes you from the basics of both languages to advanced data analysis workflows used in real-world projects.

You’ll start with Python fundamentals such as variables, data types, loops, functions, and file handling, followed by essential libraries like NumPy, pandas, Matplotlib, and Seaborn for data manipulation and visualization. You’ll also learn SQL from scratch, including SELECT, WHERE, GROUP BY, JOINs, subqueries, window functions, and advanced querying techniques.

The course includes hands-on examples where you’ll connect Python to SQL databases, import data into pandas DataFrames, perform data cleaning and exploratory data analysis (EDA), create insightful visualizations, and build end-to-end data analytics projects. By the end of this video, you’ll have the skills to work with real datasets, automate analysis tasks, and present data-driven insights.

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➡️ About Data Analyst Course

This online data analyst course will transform you into a data analytics expert. In this master’s course, you’ll learn the latest analytics tools and techniques, work with SQL, R, and Python, create impactful data visualizations, and apply statistics and predictive analytics to real business challenges.

Key Features

✅ Earn an industry-recognized Data Analyst Master’s certificate from Simplilearn
✅Learn through a comprehensive curriculum featuring exclusive Microsoft courses
✅ Learn from industry experts through live, interactive online sessions
✅ Gain hands-on experience with industry-relevant tools and packages
✅ Build real-world skills through 10+ course-end projects
✅ Apply your skills in a capstone project for holistic learning
✅ Get lifetime access to self-paced learning resources
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered
✅ Data Analytics
✅ Statistical Analysis using Excel
✅ Data Analysis using Python and R
✅ Data Visualization Tableau and Power BI
✅ Linear and logistic regression modules
✅ Clustering using KMeans
✅ Supervised Learning
✅ Unsupervised Learning

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