CHFI v8 - Computer Hacking Forensic Investigator
312-49-v8
Learn the data mining and predictive analysis essentials with hands-on techniques that turn raw data into actionable insights.
(DM-PA.AE1) / ISBN : 978-1-64459-374-5This Data Mining and Predictive Analytics course cuts through the noise to teach you the practical skills you need to analyze data and make accurate predictions. You’ll learn how to apply real-world data mining techniques, work with machine learning (ML) models, and extract insights that drive smarter decisions. We break down complex concepts into straightforward lessons to uncover the most profitable nuggets of knowledge from the data while avoiding the potential pitfalls that may cost your company millions of dollars.
34+ Interactive Lessons | 58+ Exercises | 120+ Quizzes | 164+ Flashcards | 164+ Glossary of terms
63+ LiveLab | 63+ Video tutorials | 02:02+ Hours
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Data mining is the process of discovering patterns and relationships in large datasets using statistical and ML techniques. It helps in extracting useful information from raw data.
Predictive analytics uses historical data, statistical algorithms, and ML to predict future outcomes. It builds models to forecast trends and behaviors, helping in decision-making.
Data mining helps discover patterns, trends, and insights from large data sets, enabling businesses to make informed decisions and drive efficiency.
Yes, data analysts are generally well-paid. Entry-level data analysts can earn around $40,000 to $66,000 annually, while mid-level analysts can make approximately $74,000. Senior data analysts often earn six-figure salaries, especially with specialized skills.
This data mining and predictive analysis training course is designed for data analysts, business professionals, and anyone interested in leveraging data for predictive decision-making.
As this is an intermediate to advanced level course, a basic understanding of data analysis, statistics, or programming is helpful.
This data mining and analysis training course focuses on commonly used tools like Python, R, Excel, and popular ML libraries such as scikit-learn and TensorFlow.
After completing this course, you’ll have a skillset for roles like data analyst, data scientist, business analyst, and ML engineer, among others.