Data Analysis A-Z - Become Data Analyst in 30 Days

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Free Download Data Analysis A-Z - Become Data Analyst in 30 Days
Published 10/2023
Created by Md Shahriar
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 38 Lectures ( 4h 20m ) | Size: 1.61 GB

Unlock Data Analysis with Hands-on Python Proficiency. Master Full Work-flow and Become Pro Data Analyst in 30 Days.
What you'll learn
Understand and apply the complete data analysis workflow, from data cleaning to hypothesis testing, mirroring real-life scenarios.
Develop the personal capabilities of critical thinking and problem-solving essential for effective data analysis, decision-making, and recommendation.
Implement various data analysis techniques: value counts, percentage, group by, pivot tables, correlation, and regression, practically and professionally.
Solve more than 12 real-world data analytical questions to gain hands-on experience in applying data analysis skills to diverse situations.
Learn to derive significant insights from data and use them to make informed decisions and recommendations by emphasizing the practical application.
Gain proficiency in using Python for data analysis, covering key libraries and tools commonly employed in the industry.
Learn the principles of statistical inference, understand how to draw meaningful conclusions, and make data-driven decisions based on statistical evidence.
Cultivate the ability to think critically about data, and extract meaningful insights, and deliver actionable recommendations for informed decision-making.
Requirements
No coding Experience is Needed.
Mindset to be Successful.
Dedication to be Data Analyst.
Intention to Learn Python.
Description
Embark on a transformative journey with our course, "Data Analysis A-Z: Become Data Analyst in 30 Days," where you will unravel the intricacies of data analysis from start to finish. Throughout this immersive experience, participants will gain a comprehensive understanding of the complete data analysis workflow, mirroring real-life scenarios encountered by professional data analysts.This course goes beyond technical proficiency, emphasizing the development of personal capabilities crucial for effective data analysis. From critical thinking to problem-solving, participants will acquire the skills essential for making informed decisions and recommendations based on robust data insights.The practical application of various data analysis techniques is a cornerstone of this program. Participants will dive into hands-on exercises covering value counts, percentage calculations, group by operations, pivot tables, correlation, and regression analysis, ensuring a professional mastery of these essential tools.Real-world application takes center stage as participants tackle over 12 data analytical questions, providing practical experience in applying data analysis skills to diverse situations. This emphasis on practicality extends to the extraction of significant insights from data, fostering the ability to make informed decisions and recommendations grounded in real-world application.Moreover, this course equips participants with Python proficiency tailored for data analysis. Covering key libraries and tools widely used in the industry, participants will leverage Python to manipulate and analyze data effectively. The principles of statistical inference are also covered, ensuring participants can draw meaningful conclusions and make data-driven decisions based on sound statistical evidence. Throughout the course, critical thinking remains a focal point, cultivating the ability to think deeply about data, extract meaningful insights, and deliver actionable recommendations for informed decision-making. Join us on this intensive 30-day journey and emerge as a proficient and professional data analyst.
Who this course is for
Individuals looking to kickstart their career in data analysis.
Students and recent grads in data analysis or related fields.
Professionals aiming to boost their analytical skills.
Decision-makers want to understand and leverage data analysis.
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