What will you learn in Data Science Foundations Specialization Course
Build a foundational understanding of data science processes, including data collection, analysis, predictive modeling, and algorithmic thinking using flowcharts and pseudocode.
Gain hands-on skills in Python, R, SQL, Jupyter Notebooks, and GitHub, applying them to real datasets.
Learn basic machine learning and predictive modeling, including regression and clustering.
Practice fundamental data visualization and dashboard creation.
Program Overview
1. What is Data Science?
🕒 Duration: 1 week
Topics: Defining data science and its relevance today. Introduction to data science roles and applications.
Hands-on: Reflection exercises to connect course content to real-world examples.
2. Tools for Data Science
🕒 Duration: 2 weeks
Topics: Jupyter notebooks, RStudio, GitHub, SQL, Python basics.
Hands-on: Practice labs in Jupyter and RStudio Cloud environments.
3. Data Science Methodology
🕒 Duration: 2 weeks
Topics: Nine-step data science methodology for problem solving, from business understanding to deployment.
Hands-on: Mapping a methodology to a practical case scenario.
4. Python for Data Science, AI & Development
🕒 Duration: 2 weeks
Topics: Python basics, data structures, functions, and libraries like Pandas and Numpy.
Hands-on: Writing Python scripts and using real-world data in coding exercises.
5. Databases and SQL for Data Science
🕒 Duration: 2 weeks
Topics: Relational databases, SQL queries, JOIN operations, and database design.
Hands-on: Writing SQL queries in cloud-based database tools.
6. Data Analysis with Python
🕒 Duration: 2 weeks
Topics: Exploratory data analysis, regression models, and data visualization.
Hands-on: Data manipulation with Pandas and visualizations using Seaborn/Matplotlib.
7. Data Visualization with Python
🕒 Duration: 2 weeks
Topics: Creating plots with Matplotlib, Seaborn, and Folium. Best practices in visualization.
Hands-on: Building complex, multi-layered visualizations from datasets.
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Job Outlook
Entry-level pathways: Data Analyst, Business Intelligence Associate, Junior Data Scientist, SQL Analyst.
Skills in Python, R, SQL, visualization, and ML basics are highly applicable to sectors like finance, healthcare, consulting, and public policy.
Strong credential for resumes, especially for non-technical professionals breaking into data-driven roles.
Potential salary: ₹5 L–12 L in India; $60K–$90K in the U.S. for junior analytics positions.
Specification: Data Science Foundations Specialization
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