What you will learn in Course
This course provides a job-ready introduction to data analytics, blending foundational theory with practical tools and methods.
Learners will gain hands-on experience in Python, SQL, and data visualization to solve analytical problems.
It includes statistical thinking, hypothesis testing, and data-driven decision-making principles.
A unique component is the integration of generative AI tools to speed up analysis and storytelling.
Students develop skills in wrangling, cleaning, and preparing data for accurate analysis.
The course builds confidence through real-world projects that simulate workplace analytics tasks.
The final project allows learners to demonstrate proficiency in delivering impactful business insights.
Program Overview
Foundations of Data Analytics
⏱️ 2-3 weeks
Start with understanding what data analytics is and how it supports business strategies.
Understand the data analytics process and data life cycle
Learn about key data roles and responsibilities
Identify types of data and methods of collection
Gain familiarity with tools like Python and SQL
Statistics and Data Wrangling
⏱️ 3-4 weeks
Dive into the statistical foundations that power insightful analytics.
Learn descriptive statistics and probability concepts
Explore hypothesis testing and statistical inference
Understand data wrangling processes and best practices
Prepare datasets for deeper analysis
Data Analysis and Visualization with Python
⏱️4–5 week
Explore how to manipulate and visualize data using Python and libraries.
Use pandas and NumPy to handle structured data
Perform analysis to uncover trends and insights
Build visualizations with matplotlib and seaborn
Automate analysis tasks using Python scripts
SQL for Data Analytics
⏱️ 3–4 weeks
Focus on using SQL to access, manipulate, and analyze structured data.
Write queries to filter, join, and summarize data
Perform aggregations and subqueries for deeper analysis
Combine SQL with Python workflows
Work on querying real-world datasets
Generative AI in Analytics
⏱️2–3 weeks
Integrate AI tools into your analytics process for faster and smarter outcomes.
Use generative AI to summarize findings and create reports
Enhance data storytelling through AI-driven insights
Automate repetitive data tasks with AI assistants
Understand limitations and ethics of AI in analytics
Data Analytics Capstone Project
⏱️4–5 weeks
Apply everything learned in a comprehensive project with real business data.
Analyze a dataset from start to finish
Create data visualizations to support key insights
Present findings using Python, SQL, and AI-generated reports
Build a portfolio-ready project to showcase your skills
Get certificate
Job Outlook
- Data analytics remains a high-growth field, with projected demand increasing across all sectors
- Entry-level roles in analytics offer $60K–$80K starting salaries, scaling up with experience
- Employers value practical Python, SQL, and AI-enhanced analysis capabilities
- This certification opens doors to roles like Junior Data Analyst, BI Analyst, or Marketing Analyst
- Strong foundation to move into more advanced paths like Data Science or Machine Learning
- Generative AI integration aligns with current tech trends and future hiring expectations
- Freelance and remote analytics roles are growing, adding flexibility to career options
- The certificate signals job readiness and is backed by industry leaders (DeepLearning.AI & Coursera)
Specification: DeepLearning.AI Data Analytics Professional Certificate
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