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Reviews (1740)
vaibhav shirsath
2023-09-27
Thank you for your star rating.
Pranav Mahajan
2023-09-22
In data analytics, classes typically refer to a way of organizing and structuring code to represent and manipulate data efficiently. While data analytics may not heavily use object-oriented programming (OOP) concepts as in traditional software development, classes can still be beneficial for organizing code and data processing workflows. Here's a review of classes in the context of data analytics:
Data Representation:
Classes in data analytics can be used to represent data structures such as tables, datasets, or data frames.
Attributes in these classes can correspond to columns or fields in the data.
Modularity:
Classes allow you to modularize your code by grouping related data and functions together.
This can improve code organization and make it more understandable and maintainable.
Data Processing Methods:
Classes can include methods that encapsulate common data processing tasks, such as filtering, aggregation, or transformation.
These methods can be reused across different data analysis projects.
Custom Data Types:
You can create custom classes to represent specialized data types or data structures that are commonly used in your analytics work.
For example, you might create a "TimeSeriesData" class to handle time series data with specific methods for analysis.
Visualization:
Classes can be used to encapsulate data visualization logic, allowing for the creation of reusable chart or graphing components.
Data Wrangling:
In data analytics, classes can be used to represent and manipulate data cleaning and preprocessing steps.
For instance, a "DataCleaning" class might have methods for handling missing values, outliers, and data type conversions.
Frameworks and Libraries:
Some data analytics libraries and frameworks provide their own classes for data manipulation, such as Pandas DataFrames in Python or DataFrame classes in R.
Workflow Organization:
Classes can help organize the steps of a data analytics workflow, from data ingestion and cleaning to analysis and reporting.
Each step of the workflow can be encapsulated within a class, making it easier to manage and maintain.
Collaboration:
Classes can facilitate collaboration among data analysts or data scientists by providing a standardized way to structure and share code and data processing pipelines.
Scalability:
For large-scale data analytics projects, classes can help manage the complexity of the codebase and make it easier to scale up data processing tasks.
In summary, while data analytics may not rely on classes and OOP principles to the same extent as software development, they can still be a valuable organizational tool. Classes can help you structure your code, encapsulate data processing logic, and improve code reusability and maintainability in data analytics projects.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Nilesh Kadam
2023-09-22
benefits of having good, supportive instructors in your learning journey:
Clarity of Concepts: Supportive trainers often excel at breaking down complex programming concepts into simpler, more understandable parts. They can provide clear explanations and real-world examples, helping you grasp even challenging ideas.
Motivation: Supportive instructors can boost your motivation and enthusiasm for learning. Their encouragement and positive feedback can make you feel more confident in your abilities, motivating you to tackle more complex coding tasks.
Individualized Guidance: Good trainers understand that every student has unique learning needs. They can offer personalized guidance, tailoring their teaching approach to your specific strengths and weaknesses.
Problem Solving: In programming, problem-solving is a crucial skill. Supportive trainers can guide you through problem-solving exercises, helping you develop critical thinking skills and the ability to tackle coding challenges effectively.
Accessible Resources: Supportive trainers often provide additional learning resources, such as supplementary readings, practice exercises, and coding projects. These resources can enhance your understanding and practical skills.
Interactive Learning: They may encourage an interactive learning environment, involving students in discussions, group projects, and hands-on coding exercises. This interactive approach can make learning Python more engaging and enjoyable.
Constructive Feedback: Supportive instructors offer constructive feedback on your work. They highlight areas for improvement while acknowledging your achievements, helping you continuously enhance your coding skills.
Building Confidence: Confidence is a crucial factor in programming. Supportive trainers can help you build confidence by emphasizing your successes and helping you overcome challenges in a constructive manner.
Career Advancement: A strong foundation in Python and programming principles can open doors to various career opportunities, and supportive trainers can play a significant role in helping you reach your professional goals.
Positive Learning Environment: The overall learning environment created by supportive trainers can be positive, inclusive, and encouraging. This fosters a sense of belonging and inspires students to excel.
In conclusion, having good and supportive trainers in your Python classes can make a world of difference in your learning journey. They not only help you understand Python's intricacies but also nurture your problem-solving skills, motivation, and confidence. This type of positive learning experience can have a lasting impact on your programming skills and career prospects. which all im getting from sevenmentor classes
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Anilkumar Kshirsagar
2023-09-22
In the realm of web development, Django classes are foundational components within the Django web framework, renowned for its efficiency and elegance in building web applications. Django leverages Python's object-oriented capabilities to structure and manage web application code in a highly organized manner.
Class-Based Views are a prominent feature of Django. These are Python classes that dictate how web pages should be presented or handled based on HTTP methods like GET or POST. This approach promotes reusability and clean code, making it easier to manage complex application logic.
Another vital aspect of Django classes is Model Classes. These classes define the structure of database tables, allowing developers to interact with databases using Python code rather than SQL queries. By defining models, developers can create data-driven web applications with ease, and Django takes care of the underlying database operations.
Form Classes are also crucial in Django. These classes are used to specify the structure and validation rules for HTML forms. They streamline the process of handling user input and data submission, ensuring data integrity and security.
Admin Classes are utilized to customize how data is presented and managed in the Django admin interface. Developers can define admin classes to control how models are displayed, edited, and filtered within the administrative backend, tailoring it to the specific needs of their application.
Lastly, Middleware Classes provide a means to process requests and responses globally within a Django web application. Middleware can perform tasks such as authentication, logging, or custom request/response processing, enhancing the application's functionality and security.
In summary, Django classes are an integral part of the Django web framework, enabling developers to build robust and maintainable web applications. Whether defining views, models, forms, admin interfaces, or middleware, Django's class-based approach facilitates efficient and organized web development, making it a popular choice for web developers worldwide.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Babasaheb Kshirsagar
2023-09-22
benefits of having good, supportive instructors in your learning journey:
Clarity of Concepts: Supportive trainers often excel at breaking down complex programming concepts into simpler, more understandable parts. They can provide clear explanations and real-world examples, helping you grasp even challenging ideas.
Motivation: Supportive instructors can boost your motivation and enthusiasm for learning. Their encouragement and positive feedback can make you feel more confident in your abilities, motivating you to tackle more complex coding tasks.
Individualized Guidance: Good trainers understand that every student has unique learning needs. They can offer personalized guidance, tailoring their teaching approach to your specific strengths and weaknesses.
Problem Solving: In programming, problem-solving is a crucial skill. Supportive trainers can guide you through problem-solving exercises, helping you develop critical thinking skills and the ability to tackle coding challenges effectively.
Accessible Resources: Supportive trainers often provide additional learning resources, such as supplementary readings, practice exercises, and coding projects. These resources can enhance your understanding and practical skills.
Interactive Learning: They may encourage an interactive learning environment, involving students in discussions, group projects, and hands-on coding exercises. This interactive approach can make learning Python more engaging and enjoyable.
Constructive Feedback: Supportive instructors offer constructive feedback on your work. They highlight areas for improvement while acknowledging your achievements, helping you continuously enhance your coding skills.
Building Confidence: Confidence is a crucial factor in programming. Supportive trainers can help you build confidence by emphasizing your successes and helping you overcome challenges in a constructive manner.
Career Advancement: A strong foundation in Python and programming principles can open doors to various career opportunities, and supportive trainers can play a significant role in helping you reach your professional goals.
Positive Learning Environment: The overall learning environment created by supportive trainers can be positive, inclusive, and encouraging. This fosters a sense of belonging and inspires students to excel.
In conclusion, having good and supportive trainers in your Python classes can make a world of difference in your learning journey. They not only help you understand Python's intricacies but also nurture your problem-solving skills, motivation, and confidence. This type of positive learning experience can have a lasting impact on your programming skills and career prospects. which all im getting from sevenmentor classes
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Abhishek Kshirsagar
2023-09-22
Certainly! In the context of data science, classes refer to a way of organizing and encapsulating code into reusable and structured components. Classes are typically used in object-oriented programming languages like Python to create custom data structures or models that represent real-world entities or concepts. Here's a review of classes in the context of data science:
Object-Oriented Programming (OOP):
Classes are a fundamental concept in OOP, which is widely used in data science for creating structured and maintainable code.
Attributes:
In data science, class attributes often represent data or metadata associated with a particular dataset or model.
For example, a class representing a dataset might have attributes like data, labels, and features.
Methods:
Methods within a data science class can encapsulate various data preprocessing, analysis, or visualization tasks.
For instance, a class representing a machine learning model might have methods for training, prediction, and evaluation.
Encapsulation:
Classes in data science help encapsulate data and methods, allowing for better organization and abstraction.
This encapsulation can help prevent unintended data modification and make the code more maintainable.
Inheritance:
Inheritance allows you to create a new class that is a modified version of an existing class. This can be useful for building more specialized data science models or tools.
Modularity and Reusability:
Classes promote modularity by encapsulating related functionality within a single unit.
This modularity and reusability are especially valuable in data science, where similar data manipulation or analysis tasks may be performed across different projects.
Example:
An example of a class in data science might be a "DataPreprocessor" class that includes attributes like the input data and methods for data cleaning, transformation, and feature extraction.
Another example could be a "RegressionModel" class with attributes representing model parameters and methods for training and making predictions.
Libraries and Frameworks:
Many data science libraries and frameworks, such as scikit-learn and TensorFlow, use classes extensively to define models, transformers, and other components.
In summary, classes in data science provide a structured and organized way to work with data, models, and other components. They help improve code organization, maintainability, and reusability, making it easier to develop and maintain complex data science projects.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
abhi pes yt
2023-09-22
Certainly! In the context of data science, classes refer to a way of organizing and encapsulating code into reusable and structured components. Classes are typically used in object-oriented programming languages like Python to create custom data structures or models that represent real-world entities or concepts. Here's a review of classes in the context of data science:
Object-Oriented Programming (OOP):
Classes are a fundamental concept in OOP, which is widely used in data science for creating structured and maintainable code.
Attributes:
In data science, class attributes often represent data or metadata associated with a particular dataset or model.
For example, a class representing a dataset might have attributes like data, labels, and features.
Methods:
Methods within a data science class can encapsulate various data preprocessing, analysis, or visualization tasks.
For instance, a class representing a machine learning model might have methods for training, prediction, and evaluation.
Encapsulation:
Classes in data science help encapsulate data and methods, allowing for better organization and abstraction.
This encapsulation can help prevent unintended data modification and make the code more maintainable.
Inheritance:
Inheritance allows you to create a new class that is a modified version of an existing class. This can be useful for building more specialized data science models or tools.
Modularity and Reusability:
Classes promote modularity by encapsulating related functionality within a single unit.
This modularity and reusability are especially valuable in data science, where similar data manipulation or analysis tasks may be performed across different projects.
Example:
An example of a class in data science might be a "DataPreprocessor" class that includes attributes like the input data and methods for data cleaning, transformation, and feature extraction.
Another example could be a "RegressionModel" class with attributes representing model parameters and methods for training and making predictions.
Libraries and Frameworks:
Many data science libraries and frameworks, such as scikit-learn and TensorFlow, use classes extensively to define models, transformers, and other components.
In summary, classes in data science provide a structured and organized way to work with data, models, and other components. They help improve code organization, maintainability, and reusability, making it easier to develop and maintain complex data science projects.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
SWATI KALE
2023-09-20
I have recently completed a Python course, and it was a fantastic learning experience. The course covered a wide range of topics, from basic syntax to more advanced concepts like object-oriented programming and data analysis.
The instructors were knowledgeable and engaging, making complex topics easy to understand. They provided hands-on exercises and projects that helped reinforce the material.
The course also included video lectures, quizzes, and coding assignments, which allowed me to practice what I learned. The online platform was user-friendly and had a supportive community forum for asking questions and getting help.
One aspect I appreciated was the flexibility of the course. I could study at my own pace, which was crucial for balancing work and personal life. The course materials were well-organized, making it easy to navigate and review.
By the end of the course, I felt confident in my Python skills. I could write scripts, build simple applications, and even analyze data using libraries like Pandas and NumPy.
The course's real-world applications were a highlight. I learned how Python is used in web development, automation, data science, and more. This practical knowledge made the course feel relevant and valuable.
One drawback was that the course did not cover some specialized Python topics in depth, like machine learning or web frameworks. However, it provided a solid foundation to explore these areas on my own.
In terms of cost, the course was reasonably priced for the value it offered. There were also free resources available for those on a tight budget.
Overall, I highly recommend this Python course to anyone looking to learn or enhance their Python skills. It's accessible, informative, and provides a strong foundation for future growth in Python programming.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Maithili Joshi
2023-09-19
Seven mentors encourages student participation in extracurricular activities and offers many companies and organizations. All trainers are always ready to help and they are proficient in teaching
I'm pursuing data science and machine learning course from sevenMentors. Our mentor sagar gade sir he teaches us machine learning with ease . He's always looking for student's proficiency in ML.
Machine learning seems interesting while coding but , only after the logic nd theory enlightenment .
Sir covered many topics which are not in our syllabus but these topics are useful for us. Overall teaching structure is excellent.
Coding as well as theory is coolest combination for fast grasping.
Thank you sir and sevenmentors for your support.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Sabiya Sabiya M
2023-09-19
Mentor Name: Sagar Gade
sir is teaching us Machine Learning he is good in practical as well as theoretical ,some times he also explain about python and sql language.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Karan G
2023-09-19
Currently I am pursuing my Data Science course from SevenMentor. And honestly speaking the staff here very good specially Arti Madam, Sagar Gade Sir. Concepts are very well explained and extra topics are also covered apart from the syllabus which is a plus point for students.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Vaibhav Ingole
2023-09-14
Hi I am Vaibhav recently I have completed a data analytics course and it was a wonderful experience in SevenMentor Institute. All Trainers and mentors are good and polite. It was a nice experience. All the topics were done theoretically & practically on real devices. In Data analyst you are required the tools like Python like R Python, Database management like MySQL, Spreadsheet Software like Microsoft Excel in advance, Data visualization like Power Bi or Tableau and Probability and Statics and also some libraries like Pandas, Matplotlib, NumPy and seaborn. The choice of tools depends on the specific needs of your data analysis project, your organization's preferences, and your expertise. Data analysts often use a combination of these tools to extract valuable insights from data and support decision-making processes.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Ganesh Mali
2023-09-13
Best
Niranjan Vishwanath Kapase
2023-09-13
Excellent Training! Trainers in seven Mentor are experienced and has great teaching skills. The whole training is well planned and organized Hence could cover all important points with best training. I gained a lot of confidence to attend interviews after the training.I am so happy to have a Python Training course at Seven mentor. Really, I would say that Seven Mentor is the best Python training Institute in pune, Amazing experience. I will surely recommend Seven Mentor for python training whoever wants to start career in it. The trainers would take extra time to clear our doubts
Tejas Mundhe
2023-09-13
Hi My I have completed Data Science From Seven mentor Institute Honestly speaking that it was my best decision And i am very happy with that. Seven mentor was really great. All the trainers are really good and knowledgeable. Course content are also very good. Data Analytics course covers Data Science in full breadth and depth. Also my experience with support staff was Very Good And they Are Also Supportive They Are helping us in each And Everything. They Guide And Counselling In very Good Way.
My experience at seven mentor Classes has been a wonderful. hey really do get down to the basics and explain everything in an easy to understand language for beginners I totally Understand In very Easy Way that What they Are teaching. excellent facilities and excellent tutors. I will definitely recommend this institute to my colleagues or whoever wants to pursue their career in data analytics.
I got a chance to learn "AI with Python" as part of corporate Thank you A lot Seven Mentor And All staff And Trainers.
Ajay Mali
2023-09-13
Hi My Name Is Ajay I am From Out Of Pune And I have Totally Attend Online Classes And The experience was Very Good with Seven Mentor. I joined this institute for python classes and trainer are very knowledgeable and experts in python and share real time scenarios how to implement them on practically. They conduct many mock interview in duration of training so helpful for you when you face interview. Now i am placed a good company. The python course at SevenMentor was pretty informative, classes were best and the trainer explained it with all practical examples. Thank you for giving extra knowledge about every query raised, also I learned a lot of new concepts in a practical way. The instructor was able to answer all the queries which were asked. With SevenMentor’s Job Assistance Program I was placed without any delay after the completion of the python Course.experience during the classes was too good,all the tutor were so knowledgeable and ready to clear my doubts multiple times,the way they taught us was always in new different ways so that we can understand every bit of topics fully and sometimes I was not able to attend my class ,but all the tutor's were so supportive they taught me everything on the next day when I attend the class.SevenMentor is the most trusted and best placement institute in Pune. I joined it for python training and received more than what my Expectation. Mentors are very supportive and knowledgeable. His guidance through out my training will help my further career. So Thank you so much for valuable guidance. Further faculty and management members are too much cooperative and supportive. they will help in all aspects. The trainers are supportive and friendly, concentrates on students individually. And the best part is we can attend the class of any topic if we didn't understand that in the previous class. Send the query to the teacher and you will definitely get the solution at most in small time period.
Sail Surve
2023-09-03
I have attended online RPA-UiPath batch in SevenMentor.
Faculty is really good.
Lectures are taken regularly.
Each concept have been explained properly.
Each and every doubt have been solved.
Teachers are supportive.We can contact them whenever we have doubt
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
akanksha junawane
2023-08-31
Good teaching staff and study material provided is also helpful.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Om Tilekar
2023-08-22
Excellent Training! Trainers in seven Mentor are experienced and has great teaching skills. The whole training is well planned and organized Hence could cover all important points with best training. I gained a lot of confidence to attend interviews after the training.I am so happy to have a Python Training course at Seven mentor. Really, I would say that Seven Mentor is the best Python training Institute in pune, Amazing experience. I will surely recommend Seven Mentor for python training whoever wants to start career in it. The trainers would take extra time to clear our doubts
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.
Ganesh Rakh
2023-08-21
Hi my name is Ganesh,The Advanced Excel course offers comprehensive training in mastering Excel's advanced features and functions. It equips you with the skills needed to become proficient in data analysis, financial modeling, and more.
Throughout the course, you'll delve into complex functions like VLOOKUP, INDEX-MATCH, and array formulas, empowering you to manipulate data efficiently. PivotTables are thoroughly covered, aiding in dynamic data summarization.
Furthermore, the course delves into automation with macros, streamlining repetitive tasks. Data visualization techniques, including advanced charting and conditional formatting, are also explored.
Thank you for your star rating. We appreciate you have taken the time to share your experience with us. We wish you all the very best for your future endeavors.