Data Science & AI Certificate
IDCDS

Hands-on Training from Experts Live Online

Master essential tools like Python, SQL, and machine learning to analyze data and build predictive models. You'll work on real-world projects using libraries such as pandas and scikit-learn, and gain experience with automation and AI techniques.

This program includes

  • 114 hours of live, project-based training from experts
  • Software Access
  • Additional 1-on-1 mentoring outside of class
  • Access to class recordings (30 days)
  • Verified digital certificate of completion
  • Learn at an accredited institution

Special Promotion: Receive the Python for AI: Create AI Apps with Flask & OpenAI course when you register for this certificate program. Contact us after enrolling to be added to the class.

Learn to work with databases and perform data analysis in this beginner-friendly program, designed to prepare you for entry-level roles in data science and Python engineering. Data science consistently ranks among the best and highest-paying career paths today.

  • Learn Programming Fundamentals: Master Python programming basics and explore its core data science libraries for analyzing data. Write and execute complex database queries, clean and prepare datasets for analysis, and automate tasks such as aggregating, updating, and formatting data.
  • Create Machine Learning Models: Build and evaluate machine learning models using real-world datasets. Work with Pandas to clean and balance data, apply algorithms with scikit-learn, and assess model performance to identify opportunities for improvement.
  • Make Dashboards & Visualizations: Design dynamic dashboards and data visualizations with Python libraries like Matplotlib, Seaborn, Plotly, and Dash Enterprise. Publish your projects on GitHub to showcase your skills to potential employers.
  • Industry-Aligned Projects & Mentorship: Gain hands-on experience through real-world projects that meet industry standards. Receive 1-on-1 mentoring for personalized feedback, skill refinement, and interview preparation, ensuring you’re job-ready by the end of the program.
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Add additional skills in AI for Python or data analytics:

Courses in this Certificate Program

This is the recommended order, but some courses may be taken in a different order.

Download Syllabus PDF

Unit 1 30 Hours

Python for Data Science Bootcamp
  • Learn Python fundamentals, including variables, data types, functions, loops, and control flow, for building robust programs
  • Work with complex data structures such as dictionaries and lists to efficiently organize and access data
  • Use NumPy and Pandas to import, clean, and manipulate datasets for analysis and exploration
  • Generate descriptive statistics and apply filtering, grouping, and pivoting techniques to gain deeper insights
  • Visualize data using Matplotlib and create clear, customized charts, including bar graphs, histograms, and scatter plots
  • Gain the practical skills needed to transition into machine learning with a solid understanding of data science workflows

Unit 2 18 Hours

SQL Bootcamp

Learn how to extract, filter, and manipulate data using SQL. This course covers PostgreSQL fundamentals, database querying, table joins, and advanced techniques for handling large datasets.

  • Explore information stored in a database (tables, columns, rows, etc.) using the graphical interface of DBeaver, a popular free database app.
  • Write SQL queries to retrieve data from tables in the database
  • Combine information from multiple tables using JOIN statements
  • Filter data, group it, and sort it to extract the specific information you need
  • Master advanced techniques, including subqueries, string functions, and IF‑Else logic with CASE
  • Learn how to use views and functions with parameters instead of directly querying tables

Unit 3 6 Hours

Python for Automation
  • Understand how websites are structured with HTML and CSS to identify elements for data extraction
  • Learn Python fundamentals, such as variables, data types, conditionals, loops, and list manipulation
  • Use the Requests and Beautiful Soup libraries to perform web scraping and target specific content
  • Write loops to automate web scraping across multiple pages and streamline repetitive tasks
  • Store scraped data in different formats, such as text files and CSVs, for analysis and reporting
  • Schedule Python scripts to run on a regular basis, enabling continuous data collection and automating workflows

Unit 4 24 Hours

Python Data Visualization & Interactive Dashboards

Transform raw data into interactive visual insights by building dashboards with Python’s top visualization tools. This course blends analysis, design, and deployment to help you showcase data professionally.

  • Work with real-life datasets using Python’s core libraries, including NumPy for numerical computing and Pandas for data manipulation
  • Create static and interactive visualizations using Matplotlib, Seaborn, and Plotly to clearly communicate trends and patterns
  • Build multi-component dashboards using Dash Enterprise, incorporating callbacks, sliders, date pickers, and more
  • Practice hands-on development by applying new skills to personalized projects with guided instructor support
  • Publish your dashboards online using GitHub and Heroku to demonstrate your work to potential employers or clients
  • Explore best practices for styling and structuring visual narratives that are clear, persuasive, and engaging

Unit 5 30 Hours

Python Machine Learning Bootcamp
  • Explore foundational techniques like linear and logistic regression for modeling numerical and categorical data
  • Understand the difference between regression and classification problems and when to apply each approach
  • Build and evaluate models using k-nearest neighbors, decision trees, and ensemble methods like random forest
  • Learn key concepts such as cross-validation, training vs. test sets, and performance metrics like mean squared error
  • Apply feature engineering techniques to improve model accuracy while managing overfitting and bias-variance tradeoffs
  • Use Python's essential data science libraries, NumPy, Pandas, and scikit-learn, to structure data and implement algorithms
  • Gain insights into how machine learning powers systems at companies like Netflix, Spotify, and Amazon
  • Complete a final portfolio project that demonstrates your ability to apply machine learning to solve real problems

Unit 6

Data Science Capstone Projects (Self-Paced)

Throughout this program, you will complete three capstone projects to showcase in your portfolio: 

Machine Learning & AI Capstone

  • Choose, clean, and engineer features from a structured dataset to train machine learning models (e.g., logistic regression, random forest), evaluate performance, and visualize results clearly.
  • Deliver a professional presentation detailing your data processing workflow, modeling techniques, and insights discovered using Python libraries like pandas, scikit-learn, and Matplotlib.

Python for AI Capstone (Choose One of Two)

  • AI Chat Assistant: Build an interactive chat assistant embedded on a webpage, using Flask and JavaScript to integrate with OpenAI’s API for context-aware user interactions.
  • Collectibles Identification App: Develop a Flask-based web app allowing image uploads of collectible items, leveraging OpenAI to identify items, generate descriptive metadata, and dynamically display logged session history.

Python Data Visualization Capstone

  • Clean, analyze, and visualize global CO₂ emissions alongside GDP and population data, highlighting trends and correlations through insightful visualizations with Matplotlib, seaborn, and plotly.
  • Build a responsive Dash dashboard enabling interactive exploration of emissions data, clearly communicating insights such as regional trends, GDP-emission correlations, and emission anomalies.

You will work on your capstone projects both in and outside of class, using scheduled mentoring sessions to review your progress, ask questions, and get personalized feedback from your instructor.

Attend the Python for AI course for free as part of this certificate. Choose your date after you register for the program. 

Bonus 30 Hours

Python for AI: Create AI Apps with Flask & OpenAI

Learn how to build AI-powered web applications using Flask and the OpenAI API. This course covers web development fundamentals, API integration, and AI-driven features for interactive applications.

  • Set up Flask projects and create routes for handling web requests and rendering templates.
  • Design and style web applications using HTML, CSS, and Flask’s templating system.
  • Integrate the OpenAI API to implement AI-powered features like sentiment analysis.
  • Handle user input with dynamic forms and process data for real-time interactions.
  • Implement error handling and debugging techniques to ensure smooth application performance.
  • Deploy and test Flask applications for real-world use and AI-enhanced functionality.

Schedule & Enrollment: Data Science & AI Certificate

  • 4 weeks full-time (weekdays), or 20 weeks part-time (evenings or Saturdays)
  • Price before discounts: $6,485 Full tuition: $3,995
  • Live Online
  • Payment plans
  • Software Access
  • 1:1 Mentoring included

  • Self-Paced More details
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