Rashmi Ranjan Mangaraj Data Science Trainer
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Teaching Style:
- Structured Learning: I follow a structured curriculum, beginning with the basics like statistics, and programming languages (e.g., Python), and gradually moving on to more advanced topics such as machine learning and data analysis.
- Practical Hands-On Approach: Hands-on learning by providing real-world datasets and practical exercises. Students are encouraged to apply what they learn through projects and case studies.
- Problem-Solving Orientation: Data science is about solving real-world problems. I encourage critical thinking and problem-solving skills, guiding students to use data-driven methods to tackle various challenges.
- Continuous Learning: Given the rapidly evolving field of data science, I will emphasize the importance of staying updated with the latest tools, techniques, and trends in the industry.

Methodology:
- Lecture and Discussion: I conduct lectures to explain concepts, but also promote open discussions, encouraging students to ask questions and share insights.
- Coding and Analysis: Coding is a core part of data science. I facilitate coding sessions, teaching students to write and execute code for data manipulation, analysis, and visualization.
- Projects: Assigning projects allows students to apply their knowledge in practical scenarios. It also helps in developing a portfolio, which can be valuable for future job applications.
- Feedback and Assessment: Regular feedback and assessments help gauge students' progress, identify areas where they need improvement, and offer opportunities for tailored support.

Results:
- Skill Development: I equip students with the skills to collect, clean, and analyze data, make data-driven decisions, and create meaningful visualizations.
- Job Readiness: Graduates of a data science program are prepared for data-related roles in various industries, from finance to healthcare, and can confidently tackle complex data problems.
- Research and Innovation: I inspire students to push the boundaries of data science, contributing to research and innovation in the field.

What Makes a Great Data Science Teacher:
- Passion: I am passionate about data science, conveying their enthusiasm to students and igniting their curiosity.
- Clear Communication: Effective communication is key. I explain complex concepts in a clear, understandable manner.
- Adaptability: Data science is a dynamic field. I stay connected with current industry trends and adapt their curriculum accordingly.
- Patience: Data science can be challenging. Patience is essential in guiding students through difficulties and setbacks.

Subjects

  • Data Science Beginner-Expert

Experience

  • Data Science Trainer (Nov, 2019–Present) at Silan Software
    I'm a passionate and experienced data science trainer dedicated to helping individuals and organizations unlock the power of data. With a strong background in data analysis, machine learning, and data visualization, I'm here to guide you on your data science journey.

Education

  • B.Tech (Sep, 2011–May, 2015) from IGIT SARANG Odisha–scored 7.5

Fee details

    ₹500–800/hour (US$5.90–9.43/hour)

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