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Rapid Miner: Learn and Master for Data & AnalyticsMine Mind · Last updated on Dec 23, 2024 |
Rapid Miner: Learn and Master Course for Data & Analytics offered by EduRev is a comprehensive program designed to equip learners with the skills and
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knowledge needed to become proficient in using Rapid Miner, a powerful tool for data analysis. This course covers various aspects of data and analytics, enabling participants to gain expertise in handling complex datasets and extracting valuable insights. Join this course today to enhance your data analytics skills with Rapid Miner.
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Rapid Miner: Learn and Master for Data & Analytics Exam Pattern 2024-2025
Rapid Miner: Learn and Master Exam Pattern for Data & Analytics
Introduction:
Rapid Miner is an advanced data mining tool used for extracting valuable insights from large datasets. Learning and mastering Rapid Miner is essential for professionals in the field of data and analytics. To successfully navigate through the exam pattern for Data & Analytics, it is crucial to understand the key pointers and headers that will be covered in the examination.
Exam Pattern:
The Rapid Miner exam for Data & Analytics consists of several sections, each focusing on different aspects of the tool and its applications. The exam pattern is designed to assess the candidate's knowledge and proficiency in various data mining techniques and their practical implementation using Rapid Miner.
Section 1: Fundamentals of Rapid Miner
This section tests the candidate's understanding of the basic concepts and functionalities of Rapid Miner. Key topics covered include data preprocessing, data integration, data transformation, and data modeling. Candidates should be well-versed in Rapid Miner's user interface and be able to perform basic data mining tasks.
Section 2: Data Preparation and Exploration
In this section, candidates are evaluated on their ability to prepare and explore datasets using Rapid Miner. Key points covered include data loading, data cleaning, missing value handling, and data visualization techniques. Candidates should be proficient in utilizing Rapid Miner's tools and operators for data preparation and exploration.
Section 3: Model Building and Evaluation
This section focuses on the candidate's expertise in building predictive models using Rapid Miner. Key topics covered include model selection, feature selection, model training, and model evaluation. Candidates should be able to effectively use Rapid Miner's algorithms and techniques to build accurate and reliable models for predictive analytics.
Section 4: Advanced Techniques in Rapid Miner
In this section, candidates are tested on their knowledge of advanced techniques and functionalities in Rapid Miner. Key areas covered include ensemble methods, text mining, time series analysis, and clustering. Candidates should be familiar with Rapid Miner's advanced operators and be able to apply them to solve complex data mining problems.
Section 5: Practical Application and Case Studies
The final section of the exam assesses the candidate's ability to apply Rapid Miner to real-world scenarios and case studies. Candidates will be presented with practical problems and will be required to use Rapid Miner to analyze and derive meaningful insights from the given datasets. This section aims to evaluate the candidate's problem-solving skills and practical understanding of Rapid Miner.
Conclusion:
Mastering Rapid Miner is essential for professionals in the field of data and analytics. Understanding the exam pattern and key pointers outlined above will help candidates prepare effectively for the Rapid Miner exam for Data & Analytics. It is important to dedicate sufficient time and effort to each section and practice using Rapid Miner to gain hands-on experience. With thorough preparation and a strong understanding of the tool's functionalities, candidates can confidently tackle the exam and demonstrate their expertise in data mining and analytics.
Introduction:
Rapid Miner is an advanced data mining tool used for extracting valuable insights from large datasets. Learning and mastering Rapid Miner is essential for professionals in the field of data and analytics. To successfully navigate through the exam pattern for Data & Analytics, it is crucial to understand the key pointers and headers that will be covered in the examination.
Exam Pattern:
The Rapid Miner exam for Data & Analytics consists of several sections, each focusing on different aspects of the tool and its applications. The exam pattern is designed to assess the candidate's knowledge and proficiency in various data mining techniques and their practical implementation using Rapid Miner.
Section 1: Fundamentals of Rapid Miner
This section tests the candidate's understanding of the basic concepts and functionalities of Rapid Miner. Key topics covered include data preprocessing, data integration, data transformation, and data modeling. Candidates should be well-versed in Rapid Miner's user interface and be able to perform basic data mining tasks.
Section 2: Data Preparation and Exploration
In this section, candidates are evaluated on their ability to prepare and explore datasets using Rapid Miner. Key points covered include data loading, data cleaning, missing value handling, and data visualization techniques. Candidates should be proficient in utilizing Rapid Miner's tools and operators for data preparation and exploration.
Section 3: Model Building and Evaluation
This section focuses on the candidate's expertise in building predictive models using Rapid Miner. Key topics covered include model selection, feature selection, model training, and model evaluation. Candidates should be able to effectively use Rapid Miner's algorithms and techniques to build accurate and reliable models for predictive analytics.
Section 4: Advanced Techniques in Rapid Miner
In this section, candidates are tested on their knowledge of advanced techniques and functionalities in Rapid Miner. Key areas covered include ensemble methods, text mining, time series analysis, and clustering. Candidates should be familiar with Rapid Miner's advanced operators and be able to apply them to solve complex data mining problems.
Section 5: Practical Application and Case Studies
The final section of the exam assesses the candidate's ability to apply Rapid Miner to real-world scenarios and case studies. Candidates will be presented with practical problems and will be required to use Rapid Miner to analyze and derive meaningful insights from the given datasets. This section aims to evaluate the candidate's problem-solving skills and practical understanding of Rapid Miner.
Conclusion:
Mastering Rapid Miner is essential for professionals in the field of data and analytics. Understanding the exam pattern and key pointers outlined above will help candidates prepare effectively for the Rapid Miner exam for Data & Analytics. It is important to dedicate sufficient time and effort to each section and practice using Rapid Miner to gain hands-on experience. With thorough preparation and a strong understanding of the tool's functionalities, candidates can confidently tackle the exam and demonstrate their expertise in data mining and analytics.
Rapid Miner: Learn and Master Syllabus 2024-2025 PDF Download
Syllabus for Data & Analytics Rapid Miner: Learn and Master
I. Introduction to Data & Analytics
- Understanding the importance of data and analytics in decision-making
- Overview of key concepts and terminology in data analytics
- Introduction to RapidMiner as a powerful data analytics tool
II. Data Preprocessing
- Data importing and exporting in RapidMiner
- Handling missing values and outliers
- Data cleaning and transformation techniques
- Exploratory data analysis and visualization
III. Data Mining Techniques
- Introduction to various data mining techniques
- Classification: Decision trees, Naive Bayes, k-Nearest Neighbors
- Regression: Linear regression, Logistic regression
- Clustering: K-means, Hierarchical clustering
- Association rules mining
- Time series analysis
IV. Model Evaluation and Validation
- Performance measures for classification and regression models
- Cross-validation techniques
- Overfitting and underfitting in model selection
- Model selection and hyperparameter tuning
V. Advanced Topics in Data Analytics
- Text mining and natural language processing
- Social network analysis
- Ensemble learning techniques
- Dimensionality reduction methods
- Anomaly detection
- Big data analytics with RapidMiner
VI. Real-world Applications
- Application of data analytics in various industries (e.g., finance, healthcare, marketing)
- Case studies and examples of successful data analytics projects
- Ethical considerations in data analytics
VII. Hands-on Projects
- Applying data analytics techniques using RapidMiner on real-world datasets
- Solving business problems through data-driven insights
- Developing end-to-end data analytics workflows
VIII. Conclusion and Future Directions
- Recap of key concepts and techniques learned
- Trends and advancements in data analytics
- Resources for further learning and professional development
Note: The syllabus may be subject to change based on the instructor's discretion and the needs of the participants.
I. Introduction to Data & Analytics
- Understanding the importance of data and analytics in decision-making
- Overview of key concepts and terminology in data analytics
- Introduction to RapidMiner as a powerful data analytics tool
II. Data Preprocessing
- Data importing and exporting in RapidMiner
- Handling missing values and outliers
- Data cleaning and transformation techniques
- Exploratory data analysis and visualization
III. Data Mining Techniques
- Introduction to various data mining techniques
- Classification: Decision trees, Naive Bayes, k-Nearest Neighbors
- Regression: Linear regression, Logistic regression
- Clustering: K-means, Hierarchical clustering
- Association rules mining
- Time series analysis
IV. Model Evaluation and Validation
- Performance measures for classification and regression models
- Cross-validation techniques
- Overfitting and underfitting in model selection
- Model selection and hyperparameter tuning
V. Advanced Topics in Data Analytics
- Text mining and natural language processing
- Social network analysis
- Ensemble learning techniques
- Dimensionality reduction methods
- Anomaly detection
- Big data analytics with RapidMiner
VI. Real-world Applications
- Application of data analytics in various industries (e.g., finance, healthcare, marketing)
- Case studies and examples of successful data analytics projects
- Ethical considerations in data analytics
VII. Hands-on Projects
- Applying data analytics techniques using RapidMiner on real-world datasets
- Solving business problems through data-driven insights
- Developing end-to-end data analytics workflows
VIII. Conclusion and Future Directions
- Recap of key concepts and techniques learned
- Trends and advancements in data analytics
- Resources for further learning and professional development
Note: The syllabus may be subject to change based on the instructor's discretion and the needs of the participants.
This course is helpful for the following exams: Data & Analytics
How to Prepare Rapid Miner: Learn and Master for Data & Analytics?
How to Prepare Rapid Miner: Learn and Master for Data & Analytics?
Rapid Miner is a powerful and versatile data mining tool that allows users to easily analyze and extract valuable insights from large datasets. If you are looking to enhance your skills in data analytics and become a master of Rapid Miner, the course offered by EduRev can help you achieve your goals. In this article, we will guide you on how to prepare for the Rapid Miner: Learn and Master for Data & Analytics course.
Why Rapid Miner: Learn and Master for Data & Analytics?
Rapid Miner: Learn and Master for Data & Analytics is a comprehensive course designed to equip you with the knowledge and skills required to effectively use Rapid Miner for data analysis. By enrolling in this course, you will gain hands-on experience in using various data mining techniques, building predictive models, and performing advanced analytics.
Key Points to Focus on:
1. Understanding the Basics: Before diving into the advanced concepts of Rapid Miner, it is important to have a strong foundation in the basics. Make sure to grasp the fundamentals of data mining, machine learning, and statistical analysis.
2. Exploring Rapid Miner Interface: Familiarize yourself with the Rapid Miner interface and its various components. Understand how to import, preprocess, and visualize data within the tool.
3. Learning Data Preprocessing: Data preprocessing plays a crucial role in data analytics. Gain expertise in techniques like data cleaning, handling missing values, outlier detection, and feature selection.
4. Mastering Data Mining Techniques: Rapid Miner offers a wide range of data mining algorithms. Learn how to apply and interpret these algorithms to solve real-world problems. Gain knowledge in classification, regression, clustering, and association analysis.
5. Building Predictive Models: Develop the skills to build accurate and reliable predictive models using Rapid Miner. Understand the techniques for model evaluation, optimization, and deployment.
6. Advanced Analytics: Take your data analytics skills to the next level by exploring advanced topics such as text mining, sentiment analysis, social network analysis, and time series analysis.
Preparing for the Course:
To prepare for the Rapid Miner: Learn and Master for Data & Analytics course, follow these steps:
1. Review the Course Syllabus: Familiarize yourself with the topics covered in the course syllabus provided by EduRev. Identify areas where you need to focus more and allocate time accordingly.
2. Install Rapid Miner: Download and install Rapid Miner software on your computer. Make sure it is up to date and compatible with your operating system.
3. Practice with Sample Datasets: Utilize the sample datasets provided in the course materials or find datasets online to practice your data analysis skills. This will help you become more comfortable with Rapid Miner and its functionalities.
4. Engage in Hands-on Exercises: Participate actively in hands-on exercises and assignments provided in the course. This will reinforce your understanding of the concepts and enhance your practical skills.
5. Seek Additional Resources: Supplement your learning by exploring additional resources such as books, tutorials, and online forums related to Rapid Miner and data analytics.
6. Participate in Discussions: Engage with fellow learners and instructors through online discussion forums or study groups. This will allow you to clarify doubts, share ideas, and learn from others' experiences.
Conclusion:
Preparing for the Rapid Miner: Learn and Master for Data & Analytics course requires a strong foundation in data mining concepts, hands-on practice with Rapid Miner, and a proactive approach to learning. By following the steps mentioned above and dedicating time and effort, you will be well-prepared to excel in the course and become a master of Rapid Miner in data analytics. Enroll in the course offered by EduRev today and embark on your journey towards becoming a proficient data analyst.
Importance of Rapid Miner: Learn and Master for Data & Analytics
Importance of Rapid Miner: Learn and Master Course for Data & Analytics
In today's data-driven world, the ability to effectively analyze and interpret data has become crucial for businesses and individuals alike. Rapid Miner, a powerful data mining software, has emerged as a popular choice for professionals in the field of data analytics. If you are looking to enhance your skills and master the art of data analysis, the Rapid Miner: Learn and Master Course offered by EduRev is the perfect learning opportunity.
Key Pointers:
1. Comprehensive Learning: The Rapid Miner: Learn and Master Course covers all the essential concepts and techniques required for effective data analysis. From data preprocessing to predictive modeling, you will gain a deep understanding of the entire data mining process.
2. Practical Approach: The course emphasizes a hands-on approach, allowing you to apply the concepts learned in real-world scenarios. Through practical exercises and projects, you will gain valuable experience in using Rapid Miner for data analysis.
3. Industry-Relevant Skills: Rapid Miner is widely used in various industries, including finance, healthcare, marketing, and more. By mastering this software, you will acquire skills that are highly sought after by employers in the data analytics field.
4. Versatility: Rapid Miner offers a wide range of functionalities, making it suitable for both beginner and advanced users. Whether you are just starting out or looking to enhance your existing skills, this course caters to individuals of all proficiency levels.
5. Expert Guidance: The Rapid Miner: Learn and Master Course is designed by industry experts with extensive experience in data analytics. You will receive guidance from professionals who have a deep understanding of the subject matter, ensuring a high-quality learning experience.
6. Flexibility: The course is available online, allowing you to learn at your own pace and convenience. You can access the course materials anytime, anywhere, making it ideal for working professionals or individuals with a busy schedule.
In conclusion, the Rapid Miner: Learn and Master Course offered by EduRev provides a comprehensive and practical learning experience for individuals looking to excel in the field of data analytics. By mastering Rapid Miner, you will gain industry-relevant skills and enhance your career prospects. Take the first step towards becoming a proficient data analyst by enrolling in this course today.
In today's data-driven world, the ability to effectively analyze and interpret data has become crucial for businesses and individuals alike. Rapid Miner, a powerful data mining software, has emerged as a popular choice for professionals in the field of data analytics. If you are looking to enhance your skills and master the art of data analysis, the Rapid Miner: Learn and Master Course offered by EduRev is the perfect learning opportunity.
Key Pointers:
1. Comprehensive Learning: The Rapid Miner: Learn and Master Course covers all the essential concepts and techniques required for effective data analysis. From data preprocessing to predictive modeling, you will gain a deep understanding of the entire data mining process.
2. Practical Approach: The course emphasizes a hands-on approach, allowing you to apply the concepts learned in real-world scenarios. Through practical exercises and projects, you will gain valuable experience in using Rapid Miner for data analysis.
3. Industry-Relevant Skills: Rapid Miner is widely used in various industries, including finance, healthcare, marketing, and more. By mastering this software, you will acquire skills that are highly sought after by employers in the data analytics field.
4. Versatility: Rapid Miner offers a wide range of functionalities, making it suitable for both beginner and advanced users. Whether you are just starting out or looking to enhance your existing skills, this course caters to individuals of all proficiency levels.
5. Expert Guidance: The Rapid Miner: Learn and Master Course is designed by industry experts with extensive experience in data analytics. You will receive guidance from professionals who have a deep understanding of the subject matter, ensuring a high-quality learning experience.
6. Flexibility: The course is available online, allowing you to learn at your own pace and convenience. You can access the course materials anytime, anywhere, making it ideal for working professionals or individuals with a busy schedule.
In conclusion, the Rapid Miner: Learn and Master Course offered by EduRev provides a comprehensive and practical learning experience for individuals looking to excel in the field of data analytics. By mastering Rapid Miner, you will gain industry-relevant skills and enhance your career prospects. Take the first step towards becoming a proficient data analyst by enrolling in this course today.
Rapid Miner: Learn and Master for Data & Analytics FAQs
| 1. What is RapidMiner and how does it relate to data and analytics? |  |
RapidMiner is a data science platform that allows users to easily perform data preparation, machine learning, and predictive analytics tasks. It provides a graphical interface and a wide range of tools and algorithms to help users analyze and extract insights from their data. RapidMiner is widely used in the field of data and analytics as it simplifies the process of working with large amounts of data and enables users to build and deploy predictive models without the need for extensive programming knowledge.
| 2. Can RapidMiner handle big data? | |
Yes, RapidMiner is capable of handling big data. It is designed to handle large datasets and can process data in parallel to improve performance. RapidMiner also supports distributed computing frameworks like Apache Spark and Hadoop, which allow it to scale and process data across multiple machines. Additionally, RapidMiner offers various data preprocessing techniques and algorithms that can be used to reduce the dimensionality of data and improve the efficiency of analysis on large datasets.
| 3. What are the main features of RapidMiner? | |
RapidMiner offers a range of features that make it a powerful tool for data and analytics. Some of its main features include:
- Data preparation: RapidMiner provides a set of tools for data cleansing, transformation, and integration, allowing users to prepare their data for analysis.
- Machine learning: RapidMiner supports a wide range of machine learning algorithms, including classification, regression, clustering, and association rule mining. Users can easily build predictive models and analyze their data using these algorithms.
- Text mining: RapidMiner includes text mining capabilities, allowing users to extract insights from unstructured text data.
- Visualizations: RapidMiner offers various visualization tools that help users explore and understand their data. Users can create interactive charts, plots, and dashboards to visualize the results of their analysis.
- Deployment: RapidMiner allows users to deploy their models and analysis workflows into production, making it easy to integrate data and analytics into business processes.
| 4. Is RapidMiner suitable for beginners in data and analytics? | |
Yes, RapidMiner is suitable for beginners in data and analytics. It provides a user-friendly graphical interface that does not require extensive programming knowledge. Users can build and execute analysis workflows by simply dragging and dropping components onto a canvas. RapidMiner also offers a wide range of tutorials, documentation, and online resources to help beginners get started and learn the basics of data and analytics.
| 5. Can RapidMiner be used for real-time data analysis? | |
Yes, RapidMiner can be used for real-time data analysis. It supports real-time data ingestion and processing, allowing users to analyze streaming data as it arrives. RapidMiner can connect to various data sources, such as databases, web services, and message queues, and continuously process incoming data in real-time. Users can build analysis workflows that update and produce results in real-time, enabling them to make timely and data-driven decisions.
Best Coaching for Rapid Miner: Learn and Master for Data & Analytics
If you're looking for the best coaching for Rapid Miner and want to learn and master data analytics, look no further than EduRev. EduRev offers free online coaching and study material for the Rapid Miner course and data analytics course. With their comprehensive online tutorials and downloadable PDFs, you can easily access all the important chapters and summaries of Rapid Miner and data analytics.
Rapid Miner is a powerful tool for data mining, machine learning, predictive modeling, and data visualization. With EduRev's Rapid Miner tutorial and training, you can gain in-depth knowledge of these concepts and become proficient in data analytics. Their certification program also ensures that you have the necessary skills to excel in this field.
Data analytics is a crucial aspect of business analytics, data science, and data-driven decision making. EduRev's coaching covers various topics such as data analysis, data mining techniques, data preprocessing, data cleaning, and data wrangling. You will also learn about decision trees, regression analysis, clustering analysis, classification algorithms, association rules, text mining, web mining, social media analytics, time series analysis, anomaly detection, feature selection, model evaluation, and model deployment.
What sets EduRev apart is their focus on providing quality education for free. Their online platform is user-friendly and accessible, making it convenient for students and professionals to learn at their own pace. With EduRev, you can gain the necessary skills in Rapid Miner and data analytics to advance in your career or explore new opportunities in the field of big data analytics.
So, if you're looking for the best coaching for Rapid Miner and data analytics, EduRev is the perfect choice. Start your journey towards mastering data analytics today with EduRev's free online coaching and study material.
Rapid Miner is a powerful tool for data mining, machine learning, predictive modeling, and data visualization. With EduRev's Rapid Miner tutorial and training, you can gain in-depth knowledge of these concepts and become proficient in data analytics. Their certification program also ensures that you have the necessary skills to excel in this field.
Data analytics is a crucial aspect of business analytics, data science, and data-driven decision making. EduRev's coaching covers various topics such as data analysis, data mining techniques, data preprocessing, data cleaning, and data wrangling. You will also learn about decision trees, regression analysis, clustering analysis, classification algorithms, association rules, text mining, web mining, social media analytics, time series analysis, anomaly detection, feature selection, model evaluation, and model deployment.
What sets EduRev apart is their focus on providing quality education for free. Their online platform is user-friendly and accessible, making it convenient for students and professionals to learn at their own pace. With EduRev, you can gain the necessary skills in Rapid Miner and data analytics to advance in your career or explore new opportunities in the field of big data analytics.
So, if you're looking for the best coaching for Rapid Miner and data analytics, EduRev is the perfect choice. Start your journey towards mastering data analytics today with EduRev's free online coaching and study material.
Tags related with Rapid Miner: Learn and Master for Data & Analytics
Rapid Miner, Learn and Master, Data analytics, Rapid Miner course, Data analytics course, Rapid Miner tutorial, Data analytics tutorial, Rapid Miner training, Data analytics training, Rapid Miner certification, Data analytics certification, Data mining, Machine learning, Predictive modeling, Data visualization, Big data analytics, Data science, Data analysis, Business analytics, Data mining techniques, Data preprocessing, Data cleaning, Data wrangling, Data exploration, Decision trees, Regression analysis, Clustering analysis, Classification algorithms, Association rules, Text mining, Web mining, Social media analytics, Time series analysis, Anomaly detection, Feature selection, Model evaluation, Model deployment, Data-driven decision making.
Course Description
Rapid Miner: Learn and Master for Data & Analytics 2024-2025 is part of Data & Analytics preparation. The notes and questions for Rapid Miner: Learn and Master have been prepared
according to the Data & Analytics exam syllabus. Information about Rapid Miner: Learn and Master covers all important topics for Data & Analytics 2024-2025 Exam.
Find important definitions, questions, notes,examples, exercises test series, mock tests and Previous year questions (PYQs) below for
Rapid Miner: Learn and Master.
Preparation for Rapid Miner: Learn and Master in English is available as part of our Data & Analytics preparation & Rapid Miner: Learn and Master in Hindi for Data & Analytics courses.
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Course Speciality
-Understand the concepts of Data Mining with this foundation course on Rapid MinerThe Tutorial provides introduction to data mining and step-by-step guide to Rapid Miner You will be able to understand basic Rapid Miner concepts after the completion of the course.
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01 RapidMiner Studio - GUI Intro , 09 Turbo Prep - Data Pivoting , 21 Collaboration of RapidMiner Studio and RapidMiner Server , 20 Auto Model - Clustering & Outliers , 23 RapidMiner Server Installation - Preparations , 19 Auto Model - Classification , 06 Turbo Prep - Introduction , 13 Applying the Model , 17 Optimization of the Model Parameters , 12 Creating a 'Decision Tree' Model , 14 Testing a Model , 08 Turbo Prep - Merging Data , 16 Finding the Right Model , 07 Turbo Prep Cleansing , 22 Introduction to RapidMiner Server , 10 Data Preparation , 15 Validating a Model , 02 The RapidMiner Marketplace - Product Extensions , 25 Introducing RapidMiner Radoop , 03 Visualizing Data in RapidMiner Studio , 24 RapidMiner Server Installation - Walk-through , 18 Automated Model Selection and Optimization
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Course Speciality
-Understand the concepts of Data Mining with this foundation course on Rapid MinerThe Tutorial provides introduction to data mining and step-by-step guide to Rapid Miner You will be able to understand basic Rapid Miner concepts after the completion of the course.
Full Syllabus, Lectures & Tests to study Rapid Miner: Learn and Master - Data & Analytics | Best Strategy to prepare for Rapid Miner: Learn and Master | Free Course for Data & Analytics Exam
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Rapid Miner: Learn and Master for Data & Analytics Books
Rapid Miner: Learn and Master for Data & Analytics Books is your ultimate resource for mastering the Data & Analytics Exam.
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Rapid Miner: Learn and Master for Data & Analytics Notes PDF Download
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