This is your starting point for a career in data science. No prior coding experience required.
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Duration: 8 Weeks (Part-time: ~15 hours/week)
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Learning Format: Instructor-led online cohorts with live Q&A sessions, video lectures, and a dedicated student community.
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Syllabus & What You'll Learn:
1: Introduction to Data & The Data Science Workflow
Understanding different data types (structured, unstructured).
The CRISP-DM framework for tackling data projects.
2: Python for Data Science
Core Python programming: variables, loops, functions.
Essential libraries: NumPy for numerical computing, Pandas for data manipulation and analysis.
3: Data Wrangling & Visualization
Cleaning real-world, messy data (handling missing values, duplicates).
Exploratory Data Analysis (EDA) and storytelling with Matplotlib and Seaborn.
4: Introduction to Statistics for Data Science
Descriptive statistics (mean, median, standard deviation).
Foundations of probability and inferential statistics (hypothesis testing).
Outcome: You will gain foundational skills in Python, data manipulation, and visualization, enabling you to perform basic data analysis roles and preparing you for advanced machine learning topics.