Complete, in-depth and pratical understanding of modern data analysis techniques.
What you will learn
4 Python Data Basics Intro Classes, Data Types, Loops, Conditional Statements, Functions.
Beginner to Advanced Data Cleaning, Processing and Wrangling with Pandas.
Quick Exploratory Data Analysis with Pandas Plotting PiePlot, ParallelCurves, HistPlot.
Univariate and Bivariate Analysis in Seaborn, JointPlot, BoxenPlot, SwarmPlot.
Advanced Data Exploration with Plotly; Sunburst, TreeMap, 3D ScatterPlot.
How to suppport data-driven decisions.
Hacker Statistics and Bootstrapping – Visualize to Understand Hypothesis Testing.
Data Story Telling – How to Build a Business Presentation.
LLM Job Interview Prep Game; ChatGpt, Gemini, DeepSeek, Claude, etc.
20 Interview Prep Questions by Sarah Rajani
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- Master Core Python for Data Science: Establish a strong foundation in Python programming, mastering essential syntax and data structures specifically tailored for efficient data manipulation and analytical tasks.
- Become a Pandas Data Wrangling Expert: Gain unparalleled proficiency in transforming raw, disparate datasets into clean, analysis-ready formats, effectively tackling real-world data preparation challenges.
- Unlock Rapid Insights with Exploratory Data Analysis: Develop a sharp intuition for data, leveraging Pandas’ plotting capabilities to quickly visualize key characteristics and uncover initial patterns within your datasets.
- Discover Statistical Relationships with Seaborn: Dive deep into data distributions and inter-variable correlations using advanced statistical visualizations, drawing robust, data-driven conclusions from complex information.
- Engineer Interactive Visualizations using Plotly: Elevate your data presentation by crafting dynamic, web-embeddable dashboards and plots that enable deep, interactive exploration for stakeholders.
- Drive Business Decisions with Data: Translate complex analytical findings into clear, actionable business intelligence, empowering you to significantly influence strategic outcomes with data-backed recommendations.
- Grasp Statistical Inference via Practical Simulation: Demystify hypothesis testing and confidence intervals through an intuitive, simulation-based approach, making advanced statistical concepts highly accessible and practical.
- Communicate Data Stories with Impact: Hone your ability to construct compelling narratives from your analyses, ensuring your insights resonate effectively with diverse audiences and drive organizational change.
- Accelerate Your Job Search with AI Interview Prep: Leverage cutting-edge AI tools and expert-designed questions to gain a significant competitive advantage in data analysis job interviews.
- Cultivate a Project-Ready Data Portfolio: Build a robust, practical skillset and understanding of industry best practices, equipping you to confidently tackle diverse data analysis challenges.
- PROS:
- Holistic Skill Development: Covers foundational Python, advanced analysis tools (Pandas, Seaborn, Plotly), statistical thinking, and crucial soft skills like storytelling, ensuring a well-rounded data professional.
- Highly Practical & Applied Learning: Focuses on real-world scenarios and hands-on application, preparing you to immediately contribute to data projects upon completion.
- Career-Focused Outcomes: Directly addresses job market readiness with dedicated modules on interview preparation, including innovative use of AI tools and expert guidance.
- Interactive Visualization Mastery: Empowers participants to create dynamic, engaging, and web-ready data explorations that transcend static reports.
- CONS:
- Intensive Pacing: The comprehensive curriculum and broad range of topics might present a steep learning curve for absolute beginners with no prior programming or data exposure, requiring dedicated effort.
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