Technology & IT

Data Science using Python

   Course Language: English

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Learn from : Mousita Dhar

Python, Machine Learning, Artificial Intelligence, Data Science, Core Java

BIO:

I am a passionate and results-driven professional trainer with over 16 years of progressive experience in the field of Learning & Development, Corporate Training, and Technical Education. Throughout my career, I have consistently demonstrated the ability to design, develop, and deliver impactful training solutions that align with business goals, drive performance improvements, and empower learners to achieve their full potential. My journey in training began with a deep-rooted interest in knowledge sharing and skill development. Over the years, I have had the opportunity to work with a diverse range of learners, including fresh graduates, mid-career professionals, and senior leaders. This exposure has helped me develop a unique training style that is highly engaging, learner-centric, and adaptable to various learning preferences and cultural contexts. With a strong foundation in instructional design, I have created and facilitated programs across domains such as Data Science, Artificial Intelligence, Leadership Development, Scrum and agile, and Technical Tools like Python, Java, DSA. I have also conducted domain-specific trainings in areas such as Banking, IT Services, Retail, and Healthcare, which has enhanced my ability to contextualize learning for different industries. I take pride in my ability to assess training needs, build customized learning journeys, and use blended learning methodologies that combine classroom training, online modules, hands-on projects, and assessments. My sessions are known for their clarity, interactivity, and practical relevance, often supported by real-life case studies, live demonstrations, and collaborative exercises. Over the years, I have worked closely with cross-functional teams including HR, Operations, Quality, and Technology to drive organization-wide L&D initiatives. Some of the notable programs I’ve led include onboarding and induction training, leadership acceleration programs, upskilling tracks for digital transformation, and capability development frameworks for high-potential employees. I stay updated with the latest trends in training technology, adult learning theories, and industry best practices to ensure that my training interventions are modern, relevant, and measurable. In addition to my training responsibilities, I have also played mentoring and coaching roles, supporting learners in their career development, goal setting, and overcoming workplace challenges. My communication skills, empathy, and commitment to learner success have often been highlighted in feedback and evaluations. What truly motivates me as a trainer is the transformative power of education. I believe that the right training at the right time can not only enhance skills but also build confidence, shift mindsets, and unlock new possibilities. Whether I’m working with a team of new hires or senior professionals, I approach each session with the same level of enthusiasm, preparation, and a learner-first mindset. In summary, I bring to the table a rich blend of technical expertise, instructional experience, and a passion for continuous learning. I look forward to opportunities where I can contribute to individual growth, organizational capability building, and the creation of future-ready talent through meaningful and impactful training engagements.

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Course Description:

Course Summary:

This comprehensive course is designed to provide learners with a strong foundation in Data Science using the Python programming language. It covers the complete data science lifecycle including data collection, cleaning, exploration, visualization, modeling, and deployment. The course combines theoretical knowledge with practical applications to help learners understand how to solve real-world problems using data.

Participants will gain hands-on experience with popular Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, and Statsmodels. By the end of the course, learners will be able to perform data analysis, build and evaluate machine learning models, and communicate insights effectively.

Target Audience:

  • Students and fresh graduates interested in data science

  • Working professionals aiming to switch to a data-centric role

  • Analysts and developers looking to upskill in Python-based data science tools

Prerequisites:

  • Basic understanding of Python programming

  • Familiarity with high school level mathematics and statistics

Course Duration:

8–12 weeks (flexible)

Tools & Technologies Used:

  • Languages: Python

  • Libraries: NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn

  • Platforms: Jupyter Notebook, Google Colab, Visual studio code, Spider

Key Learning Outcomes:

  • Understand the data science workflow and its components.

  • Perform data manipulation and analysis using Pandas and NumPy.

  • Visualize data using Matplotlib and Seaborn.

  • Apply statistical methods for data exploration and inference.

  • Build machine learning models using Scikit-learn.

  • Evaluate model performance using appropriate metrics.

  • Apply feature engineering and model tuning techniques.

  • Work with real-world datasets and case studies.

Course Curriculum:

  1. Data Science foundation
  2. introduction to Python
  3. Basic Statistics 
  4. Data Analysis using Python, Excel
  5. Machine learning basic
  6. Machine learning expert
  7. Advanced Data Science
  8. Databases : SQL, MongoDB
  9. Big data foundation
  10. Business Intelligence (Power BI)

Start Date

Course Duration

9 Weeks

Total Number of Classes

18

Course Frequency

WEEKLY

Course Fee

$174.00

Post Course Support

  • Assignments
  • Forums
  • Quizzes
  • Resources
  • Recorded Session Videos

Earn a Course Completion Certificate

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