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Data Science - Live Project: Gain real-world, on-the-job experience

Work as a data scientist on 3 live projects each spanning ~8 weeks and stand out from the crowd, with a letter of recommendation from an industry expert. Enhance your technical proficiency and increase your employability, through our program inspired by the Team Data Science process devised by Microsoft

3 hands-on live projects mentored by industry experts

Operate in a real-world scenario & get a letter of recommendation

Learn to utilize industry-relevant tools

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Why take up this course?

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Analytical Thinking

Formulate business-relevant questions and conduct thorough data analysis to provide actionable insights.

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Data Management

Understand data preprocessing, handling missing values, and employing exploratory data analysis techniques to interpret findings effectively.

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Presentation Skills

Prepare and present your final report, complete with visualizations and evidence-based conclusions, to decision-makers in the real estate sector.

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Team Collaboration

You’ll work in small groups (4-6 learners), breaking down tasks into manageable parts, and engaging in peer learning to enhance your analytical skills.

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Tools You Will Learn

Python libraries: NumPy, Pandas, and Data Visualization tools. Jupyter notebooks for coding and documentation

Data Science: Sprint Projects Syllabus

What will you learn?

Top-notch and up-to-date live projects taught by renowned industry experts using hands-on projects, and live sessions.

Skills Acquired: Data cleaning, preprocessing, Python, NumPy, and Pandas.

Skills Acquired: SQL for data extraction, Power BI/Tableau for visualization, data storytelling.

Skills Acquired: Machine learning algorithms, model optimization, predictive analysis.

5-6

Months

3

Live Projects

Industry Expert Sessions

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Business Analysis & Data Preparation

7 weeks

1 Project

Business Analysis & Data Preparation

Focus: Identify key business questions and extract actionable insights.

Sample: Analyze real estate datasets (e.g., property prices, sales trends).

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Data Cleaning & Advanced Visualization

8 weeks

1 Project

Data Cleaning & Advanced Visualization

Focus: Clean, prepare, and analyze data with dashboards and reports.

Sample: Analyze e-commerce data to understand customer purchase behaviors.

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Machine Learning & Predictive Analysis

8 weeks

1 Project

Machine Learning & Predictive Analysis

Focus: Develop models to predict trends and solve business problems.

Sample: Use time series analysis to forecast sales for a retail chain, accounting for seasonal trends.

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Letter of Recommendation

Earn valuable credentials and recognition

Secure a Letter of Recommendation from an industry expert to enhance your resume and profile, demonstrating your skills and professional value

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Letter of Recommendation

Widely recognized and valued

Top Recruiters

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Disclaimer

  1. The above statistics depend on various factors and individual results may vary. Past performance is no guarantee of future results.

  2. The student assumes full responsibility for all expenses associated with visas, travel, & related costs. upGrad does not .