Pune a thriving hub for technology and innovation offers a variety of data science courses tailored to individuals at different stages of their careers. While the AI of mastering data science is similar, the strategies and course frameworks of freshers and seasoned experts vary greatly. To be able to understand the differences, followed by customized guidance for choosing your custom-fit course. Regardless of your expertise level, selecting the best classes for data science in Pune can be crucial for your success. 

1. Course Content and Coursework: One of the major differences between data science classes for freshers and experienced professionals resides in the course content and coursework. These courses emphasize foundational skills

• For Freshers- 

1. Learning languages like Python, and R is very important for practicing data science. 
2. It also focuses on mathematics and statistics. These are the foundational topics that talk about probability, linear algebra, and calculus, which are the backbone of machine learning algorithms. 
3. It is important to learn data cleaning, data manipulation, and data organization as a fresh data science expert.
4. These individuals are also introduced to the fundamental machine learning concepts. 
5. Data visualization helps organizations to know the benefits and drawbacks of their businesses so that they can improve further. The data visualization tools like PowerBI and Tableau are taught in this program.

• For Experienced-

1. Advanced Machine Learning Algorithms- It consists of deep learning, natural language processing, and reinforcement learning.
2. Big Data Technologies- The establishment of tools like Hadoop, Spark, and Google Cloud, for large-scale data processing.
3. Algorithms Optimization- It is the methodologies for enhancing the performance and scalability of ML models.
4. Domain-Specific Applications- Experts are subjected to learning to implement data science techniques in specific industries like marketing, finance, healthcare, etc.
5. Real-World Case Studies- Experienced aspirants are given a set of more complex, industry-oriented case studies that need detailed data science methodologies. 

2. Learning Objectives and Outcomes: The results of the data science learning vary based on their respective career objectives. With the similar goal of upskilling, the extent of expertise and complex training they obtain differ for novice and seasoned professionals.

• For Freshers-

1. Constructing a Strong Base- These individuals tend to obtain knowledge in programming, statistics, and basic machine learning. 
2. Portfolio Development- The courses focusing on freshers often subject them to beginner-level projects and case studies to exhibit hands-on skills to potential recruiters. 
3. Certification- Acquiring industry-recognized certifications helps in improving the job possibilities of fresh data science aspirants. 
4. Job Readiness- The course for freshers also prepares aspirants for entry-level data science roles like data analyst, junior data scientist, etc. 

• For Experienced-

1. Deepening Existing Knowledge- Learning these will allow us to solve complex business problems. 
2. Data Science Applications in their Current Roles- It educates on how to apply new proficiencies to improve their performance in existing job functions, especially for experts in data-heavy roles such as business analysis, IT, or software engineering.
3. Specialization- After a certain number of experience in the data science field, experienced individuals need to undergo specialization in a particular niche like machine learning, AI, big data, etc. 
4. Professional Advancements- Some dedicated mentors guide the expert to senior data science job roles like data science manager, senior data scientist, AI/ML specialist, etc. The non-tech professionals can also look for a transition into the data science field. 

3. Mode of Learning: The choice of the mode of learning is subject to individual preferences, but still it also varies from experienced learners to fresh learners. The learning mode comprises offline, online, and hybrid learning.

• For Freshers-

1. Classroom Learning- This type of learning offers a structured format with direct instruction from the instructor and peers.
2. Apprenticeships and Bootcamps- The data science program for freshers often involves apprenticeships and boot camps to provide hands-on training. It helps to construct the portfolio required for getting jobs in the industries.
3. Full-Time Learning- The fresh graduates have comparatively much time on their hands, that they can dedicate to full-time sessions. 

• For Experienced-

1. Online Learning- The online data science certification courses provide the much-needed flexibility for working individuals, who have limited time for classroom sessions. 
2. Weekend Courses- These best classes for data science in Pune are specifically curated to accommodate experts with packed schedules, permitting them to upskill without stopping their professional commitments.
3. Executive Programs- The data science courses also focus on the need of experts who want to get qualified for senior roles. Thus, often focus on project management and other interpersonal development along with advanced technical learning.

Conclusion

The purpose of all data science classes in Pune is to serve both freshers and experienced professionals. The difference in data science curriculums comes from course content, projects, and the extent of the training. The training of a fresh graduate is more about fundamental concepts, beginner-level projects, and guiding for job roles with basic skill sets. However, the data science training of expert individuals comprises specializations, project management skills, machine learning algorithms, deep learning, NLP, etc. Try to understand this difference and find the best fit that suits your career objectives.