What you will learn
- Understand the fundamentals of data science, statistics, and machine learning.
- Learn how to work with structured and unstructured data using industry-standard tools.
- Gain hands-on experience with Python, SQL, and data visualization techniques.
- Explore key concepts like data wrangling, exploratory data analysis (EDA), and feature engineering.
- Understand machine learning basics, including regression, classification, and clustering.
- Work on real-world datasets and develop insights using practical case studies.
- Complete a capstone project to apply data science skills in a business scenario.
Program Overview
Foundations of Data Science
⏱️4-6 weeks
- Learn the core principles of data science and its applications across industries.
- Understand different types of data, databases, and data collection methods.
- Introduction to Python programming and SQL for data manipulation.
Data Cleaning & Exploration
⏱️ 6-8 weeks
- Learn data wrangling techniques to clean and prepare messy data.
- Work with Pandas and NumPy for data transformation.
- Understand how to identify outliers, missing values, and inconsistencies.
Exploratory Data Analysis (EDA)
⏱️ 6-8 weeks
- Apply statistical methods to extract insights from data.
- Use Matplotlib and Seaborn for data visualization.
- Learn how to create histograms, scatter plots, and correlation heatmaps.
Machine Learning Basics
⏱️ 8-12 weeks
- Introduction to supervised and unsupervised learning techniques.
- Learn about linear regression, decision trees, and clustering methods.
- Apply machine learning models using Scikit-learn and TensorFlow.
Capstone Project
⏱️ 12-15 weeks
- Work on a real-world data science project from start to finish.
- Use Python, SQL, and visualization tools to analyze and interpret data.
- Present findings through reports and dashboards.
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Job Outlook
- High Demand: Data science is among the fastest-growing careers, with a 35% job growth rate by 2030.
- Salary Potential: Entry-level data scientists earn $85K – $120K per year, with experienced professionals making $150K+.
- Industry Applications: Data science is widely used in finance, healthcare, tech, and marketing.
- Career Opportunities: Prepares learners for roles like Data Scientist, Data Analyst, Machine Learning Engineer.
Specification: Introduction to Data Science Specialization
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