Google Advanced Data Analytics Professional Certificate

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Coursera Study Guide

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table of CONTENT

1. Foundations of Data Science

The first course in the Google Advanced Data Analytics Certificate, this program is designed as the foundation for acquiring the skills necessary to pursue advanced roles in data analytics, including positions such as entry-level data scientist or advanced-level data analyst. The curriculum equips participants with the expertise to analyze data effectively, empowering them to contribute to informed decision-making processes within businesses.

2. get started with python

This course marks the second installment in the Google Advanced Data Analytics Certificate, a comprehensive series comprising seven courses. Focusing on the Python programming language, participants will gain proficiency in fundamental concepts of Python programming and its applications in data analysis. The curriculum encompasses crucial topics such as object-oriented programming, variables, data types, functions, conditional statements, loops, and data structures. Through this course, participants will develop practical skills aligning with the industry expectations of data professionals who leverage Python for effective data analysis.

3. Go Beyond the numbers: translate data into insights

This represents the third module within the Google Advanced Data Analytics Certificate, a comprehensive series of seven courses. Throughout this course, participants will master the art of uncovering narratives within data and skillfully presenting these stories to captivate audiences. The curriculum delves into the strategies employed by data professionals in utilizing storytelling as a tool for deeper comprehension of data and conveying pivotal insights to both team members and stakeholders. Moreover, participants will engage in hands-on practice of exploratory data analysis techniques and acquire the skills to craft impactful data visualizations, aligning with the proficiency standards expected of data professionals.

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4. The Power of Statistics

This marks the fourth installment in the Google Advanced Data Analytics Certificate, a comprehensive seven-course program. Throughout this course, participants will delve into the world of statistics, unraveling its significance in the hands of data professionals for robust data analysis and insightful discoveries. Key concepts covered include descriptive and inferential statistics, probability, sampling, confidence intervals, and hypothesis testing. Additionally, participants will gain practical experience using Python for statistical analysis, honing their skills in both computation and effective communication of findings, aligning with the standards of data professionals.

5. Regression Analysis: Simplify Complex Data Relationships

The fifth course in the Google Advanced Data Analytics Certificate, this module focuses on regression analysis, a pivotal tool for data professionals. Participants delve into the intricacies of uncovering relationships among variables within datasets, pinpointing critical factors influencing business performance. Through practical exercises, learners gain proficiency in modeling variable relationships and explore diverse data modeling methods tailored to address business challenges. The curriculum encompasses key techniques like linear regression, analysis of variance (ANOVA), and logistic regression, providing a comprehensive understanding of advanced analytical approaches.

6. The Nuts and Bolts of Machine Learning

As the sixth module in the Google Advanced Data Analytics Certificate, this course illuminates the realm of machine learning—a transformative field employing algorithms and statistical techniques to enable computer systems to discern patterns within data. With a focus on empowering data professionals, the curriculum delves into the practical applications of machine learning in analyzing vast datasets, resolving intricate problems, and making precise predictions. Participants gain insights into the two primary types of machine learning: supervised and unsupervised, equipping them to apply various models, including Naive Bayes, decision trees, random forest, and more, to address diverse business challenges.

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7. Google Advanced Data Analytics Capstone

As the culminating module in the Google Advanced Data Analytics Certificate, this seventh course offers participants the chance to undertake an optional capstone project. Drawing on the key concepts acquired in the preceding six courses, the capstone project serves as a practical application of the newly acquired skills and knowledge. Participants are tasked with leveraging their expertise to generate data-driven insights tailored to address a specific business problem. This hands-on experience provides a comprehensive opportunity to synthesize the diverse elements of the program and showcase proficiency in real-world scenarios.

  • Module 1 – Capstone Project (Only Projects)
  • Module 2 – Data-focused career resources (Only Projects)
  • Module 3 – Put your Advanced Data Analytics Certificate to work (Only Projects)

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