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What You'll Learn

Real-world use cases of Python and its versatility.
Installation of Python on both Mac and Windows operating systems.
Fundamentals of programming with Python
including variables and data types.
Working with various operators in Python to perform operations.
Fundamental concepts and importance of statistics in various fields.
How to use statistics for effective data analysis and decision-making.
Introduction to Python for statistical analysis
including data manipulation and visualization.

Requirements

Students should have a general understanding of how to operate a computer.
Be comfortable with common tasks like file management and using a web browser.
No Prior Programming Experience Required.
A basic understanding of mathematics
including algebra and arithmetic.
Familiarity with fundamental concepts in data analysis and problem-solving.

Description

Embark on a transformative journey into the dynamic realm of Data Analytics and Visualization, where you will acquire essential and sought-after tech skills. This comprehensive course is designed to empower you with proficiency in key tools and methodologies, including Python programming, Excel, statistical analysis, data analysis, and data visualization.

Key Learning Objectives:

- Gain hands-on experience in Python, a powerful and versatile programming language widely used for data analysis and manipulation.

- Learn to leverage Python libraries such as Pandas and NumPy for efficient data handling and manipulation.

- Develop advanced skills in Excel, exploring its robust features for data organization, analysis, and visualization.

- Harness the power of Excel functions and formulas to extract insights from complex datasets.

- Acquire a solid foundation in statistical concepts and techniques essential for making informed decisions based on data.

- Apply statistical methods to interpret and draw meaningful conclusions from data sets.

- Explore the entire data analysis process, from data cleaning and preprocessing to exploratory data analysis (EDA) and feature engineering.

- Learn how to identify patterns, outliers, and trends within datasets, enabling you to extract valuable insights.

- Master the art of presenting data visually through a variety of visualization tools and techniques.

- Use industry-standard tools like Matplotlib and Seaborn to create compelling and informative data visualizations.

Upon completion, you will possess a well-rounded skill set in data analytics and visualization, equipping you to tackle real-world challenges and contribute meaningfully to data-driven decision-making in any professional setting. Join us on this journey to become a proficient and sought-after tech professional in the field of data analytics and visualization.

Who this course is for:

Beginners with no prior programming experience.
Students or professionals in various fields
including business
science
social sciences
and healthcare
who want to enhance their data analysis skills.
Anyone interested in automating tasks or data analysis.
Data analysts
researchers
and scientists seeking to strengthen their statistical foundations and Python programming skills.
Beginners with no prior statistical knowledge but with a curiosity to learn and apply statistical methods.
Professionals looking to advance their career by acquiring valuable statistical and data analysis skills.