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Predictive Data Analysis

Ivan Vega, Joseph Lozada, and Daniel Roca

Gain new skills & unlock the power of Predictive Data Analysis with Udacity's online training course. Master the techniques used by data professionals today.

Prerequisite details

To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:

Data transformation
Basic descriptive statistics
Data visualization
Power BI Proficiency
Chart types
Data wrangling
Elementary algebra

Gain new skills & unlock the power of Predictive Data Analysis with Udacity's online training course. Master the techniques used by data professionals today.

Prerequisite details

Data transformation
Basic descriptive statistics
Data visualization
Power BI Proficiency
Chart types
Data wrangling
Elementary algebra

You will also need to be able to communicate fluently and professionally in written and spoken English.

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Bootcamp level quality

Complete hands-on projects and get personalized feedback with Udacity.

What's inside

Syllabus

This lesson will introduce predictive analytics concepts and a general overview of when to use it in your organization. We will also review the project and the primary tool we will use: Power BI.

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Develops skills that directly translate into career progression in data science

Course content is relevant for data professionals, analysts, and data scientists alike

Taught by experts in Predictive Data Analysis who are recognized for their work in the field

Part of a larger data science course collection offered by Udacity

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Reviews summary

Predictive data analysis with power bi

According to students, this course offers a very practical approach to predictive data analysis using Power BI. Learners particularly highlight the hands-on project work and the application of core machine learning techniques like regression and time-series forecasting. While many find the instructor explanations clear and the content valuable for professionals, a significant number of reviews suggest a challenging learning curve for those without strong prior knowledge. There's a notable split: some feel it provides a solid foundation for Power BI users, while others find the theoretical depth insufficient for a robust understanding of ML models, urging the need for supplementary study.

Instructor's clarity is generally praised, but some sections could benefit from more detail.

"The instructor explained complex topics very clearly."

"The instructor's examples were clear and easy to follow."

"I think the instructor could have spent a bit more time on interpreting the statistical outputs for some of the models..."

"Some parts felt a bit rushed, especially the AutoML features, but overall a solid foundation."

Offers valuable practical experience through a realistic final project.

"I appreciated the hands-on project which solidified my understanding."

"The final project on flight delays was challenging but very rewarding, allowing me to apply all learned concepts."

"The hands-on labs and project were key to grasping the material."

"The project was great for hands-on experience and very realistic."

Focuses on the real-world application of predictive analytics in Power BI.

"This course provided an excellent deep dive into predictive analysis using Power BI."

"Absolutely brilliant! The practical applications shown in Power BI are incredibly valuable."

"A very practical course for using Power BI in predictive analysis. I particularly enjoyed the regression and time-series modules..."

"I learned how to use practical tools and strategies that I could apply immediately to my work."

Emphasizes Power BI features over deep statistical or ML theoretical insights.

"While Power BI is used, I expected more rigorous statistical explanations."

"The course introduces predictive analytics concepts but doesn't go deep enough into the underlying theory."

"If you'm looking for a quick run-through of Power BI's capabilities... if you want a robust understanding of machine learning models, you'll need to supplement this course heavily."

"I felt the content was superficial for predictive analysis and more like a Power BI features tutorial."

Opinions vary on the necessary prior knowledge; challenging for some beginners.

"Disappointed. I felt the course assumes too much prior knowledge, especially beyond basic Power BI."

"This course is not for true beginners. The prerequisites are listed but the instruction assumes a much higher level of data science understanding."

"Prerequisite knowledge in Power BI is definitely essential."

"I struggled with the pace and found myself lost quickly, as the content relies too heavily on Power BI functions without explaining the 'why'."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Predictive Data Analysis with these activities:

Create a Course Study Guide

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Organize and summarize key concepts to enhance retention and understanding.

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Review course materials
Identify important topics and concepts
Create summaries and notes

Review Statistics

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Review statistics concepts for a better understanding of the course materials.

Browse courses on Descriptive Statistics

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Read a textbook chapter on statistics
Complete practice problems
Take a practice test

Participate in Power BI workshops

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Attend workshops to develop hands-on skills and industry best practices.

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Find Power BI workshops
Register and attend workshops
Practice and implement learned techniques

Three other activities

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Practice Power BI

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Practice using Power BI to reinforce the concepts learned in the course.

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Download and install Power BI
Complete tutorials on Power BI
Practice creating visualizations and reports

Learn Time Series Forecasting

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Explore time series forecasting techniques to enhance understanding of the course materials.

Browse courses on Time Series Analysis

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Find tutorials on time series forecasting
Follow the tutorials and complete exercises
Apply the techniques to real-world data

Create a Predictive Analytics Report

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Create a comprehensive report that includes data analysis, visualization, and recommendations.

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Gather and clean data
Perform data analysis and modeling
Create visualizations and dashboards
Develop recommendations and insights

Career center

Learners who complete Predictive Data Analysis will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists research and develop new and innovative data analysis techniques that can be used to solve real-world problems. Predictive Data Analysis (PDA) is a subfield of data science that focuses on developing models that can predict future events. Studying PDA can open up a rewarding career as a Data Scientist. This course will help you master the techniques used by Data Scientists today, including data transformation, descriptive statistics, data visualization, and machine learning algorithms like regression and classification.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers are responsible for building, deploying, and maintaining machine learning models. PDA is a fundamental skill for Machine Learning Engineers, as it allows them to develop models that can predict future events and make decisions. Studying PDA can help you gain the skills you need to succeed as a Machine Learning Engineer. This course will help you develop a solid foundation in PDA.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts use data to solve business problems and identify opportunities. The ability to predict future events is a valuable skill for Data Analysts to have. By studying PDA, you can open up doors to new opportunities for you as a Data Analyst. PDAs can be a cornerstone in building effective solutions to address business problems.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians use data to understand the world around us. Probability, an essential subfield of statistics, is a key concept behind predictive modeling. PDA is a subfield of statistics that focuses on developing models that can predict future events. This course will help you become more familiar with PDA and enhance your expertise as a Statistician.

See salaries and explore the career path for Statistician

Financial Analyst

Financial Analysts use data to make investment decisions. The ability to predict future events can give Financial Analysts a leg up in the competitive world of finance. This course will help you gain the skills you need to succeed as a Financial Analyst.

See salaries and explore the career path for Financial Analyst

Business Analyst

Business Analysts use data to help businesses make better decisions. PDA can help Business Analysts gain insights into future trends. This course will help you develop the skills you need to succeed as a Business Analyst.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

Operations Research Analysts use data to optimize business processes. The ability to predict future events can help Operations Research Analysts make better decisions that improve efficiency.

See salaries and explore the career path for Operations Research Analyst

Data Engineer

Data Engineers are responsible for building and maintaining the infrastructure that stores and processes data. PDA is a valuable skill for Data Engineers to have, as it allows them to design systems that can handle large volumes of data and quickly generate predictions.

See salaries and explore the career path for Data Engineer

Software Engineer

Software Engineers design, develop, and maintain software applications. PDA is a valuable skill for Software Engineers to have, as it allows them to develop applications that can make predictions and learn from data.

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Quantitative Analyst

Quantitative Analysts use data to make investment decisions. PDA is a valuable skill for Quantitative Analysts to have, as it allows them to develop models that can predict future market movements.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use data to assess risk and determine insurance premiums. PDA is a valuable skill for Actuaries to have, as it allows them to develop models that can predict future events and assess risk.

See salaries and explore the career path for Actuary

Epidemiologist

Epidemiologists use data to study the distribution and determinants of health-related states or events in specified populations. Time-series analysis, a key component of PDA, is widely used in the field of epidemiology to estimate trends and predict future outbreaks.

See salaries and explore the career path for Epidemiologist

Market Research Analyst

Market Research Analysts use data to understand consumer behavior and trends. PDA is a valuable skill for Market Research Analysts to have, as it allows them to develop models that can predict future demand.

See salaries and explore the career path for Market Research Analyst

Risk Manager

Risk Managers use data to identify and assess risks. PDA is a valuable skill for Risk Managers to have, as it allows them to develop models that can predict future events and assess risk.

See salaries and explore the career path for Risk Manager

Insurance Underwriter

Insurance Underwriters use data to assess risk and determine insurance premiums. PDA is a valuable skill for Insurance Underwriters to have, as it allows them to develop models that can predict future events and assess risk.

See salaries and explore the career path for Insurance Underwriter

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Predictive Data Analysis.

Machine Learning with R

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Provides a comprehensive overview of machine learning techniques, with a focus on R programming. It valuable resource for students who want to learn more about the practical applications of machine learning.

Predictive Data Analysis

Prerequisite details

Prerequisite details

Here's a deal for you

What's inside

Syllabus

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Reviews summary

Predictive data analysis with power bi

Activities

Career center

Reading list

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