New cohort starts September 2026 Online, live · Taught in English Earn a U.S. diploma
Data Science & Applied AI Bootcamp

Don't just use AI. Learn to build with it.

A 156-hour part-time program across 11 sequential courses, six taught by Lid Vizion AI, an active Miami AI studio. Go from your first line of Python to a deployable data system.

Starts Sep 5, 2026 · Mon & Wed, 18:00–20:00 · Taught in English
data_pipeline.run()
156
clock hours
11
courses
6
portfolio projects
INGESTSQL · API · CSV
TRANSFORMPython · Pandas
SERVEML · dashboards

Tools used in real production environments, not toy examples

ClaudeClaude CodeChatGPTCursorPostgreSQLSupabaseSQLitePythonPandasMetabasen8nGitHubRoboflowPostman
Why this program is different

Built by practitioners who deploy AI

Every concept comes from systems Lid Vizion AI has already built and shipped for real clients.

01

Built by practitioners who deploy AI

Lid Vizion AI runs 12 live production deployments and a University of Miami computer vision research partnership. You learn from systems they have shipped.

02

AI + data + operations in one track

Most programs teach data or AI in isolation. This bootcamp bridges AI fundamentals, SQL, Python, machine learning, and automation into one coherent progression.

03

70% hands-on build, every session

Each 2-hour session is 30% context and 70% live build lab. You run real queries and deploy actual workflows during class, not after it.

04

Portfolio-driven from day one

Every project ships a real artifact: a SQL dashboard, a Python pipeline, an analytics dashboard, a machine learning model. The capstone ties it all together.

05

100% U.S. lecturers

Live Track students with 80% attendance earn a U.S.-recognized diploma and study alongside an international Miami cohort.

Curriculum

11 courses. One full-stack data & AI skillset.

From your first line of Python to a production-ready data platform. Six modules are taught by Lid Vizion AI, the rest by Creative Hub faculty.

  • What AI and data science are: the data lifecycle and data-driven decisions
  • How businesses use AI: support automation, document review, inventory analytics, computer vision
  • The modern AI stack: APIs, databases, automation, dashboards, decisions
  • AI tools setup: ChatGPT, Claude, and Cursor, your core toolkit
  • First hands-on lab: build your AI workspace and automate a repetitive task
  • Structured vs unstructured data and common business workflows
  • From spreadsheets to databases: tables, rows, IDs, and relationships
  • ETL: mapping raw data from source to cleanup to destination
  • Data cleaning and validation: duplicates, missing values, validation rules
  • APIs for beginners: requests, responses, endpoints, and JSON
  • Integration mapping and workflow automation diagrams
Project

Data integration workflow: a cleaned dataset, ETL diagram, and data dictionary.

  • What SQL is and when to use databases over spreadsheets
  • Tables, rows, columns, data types, primary and foreign keys
  • Core queries: SELECT, FROM, WHERE, ORDER BY, LIMIT
  • Aggregations: COUNT, SUM, AVG, GROUP BY and HAVING for KPIs
  • JOINs: connecting data across multiple tables and systems
  • Cloud databases with PostgreSQL and Supabase, plus AI-assisted SQL
Project

SQL data cleaning and querying project on a real business dataset.

  • Turning operational data into reporting systems and dashboards
  • Designing BI solutions: KPIs, metrics frameworks, report structures
  • Dashboard development: charts, filters, slicers, interactive reporting
  • Connecting BI tools to live databases and automating delivery
  • Reading BI outputs: understanding what the data is telling you
  • Structuring a data narrative with insight and recommendation
  • Presenting to technical and non-technical audiences
  • Translating data into clear, actionable business recommendations
  • Using AI for forecasting, performance analysis, and optimization
  • AI-assisted analytics workflows with Claude and ChatGPT
  • Identifying where AI adds the most value in analytics
  • Descriptive statistics: mean, median, variance, distributions
  • Inferential statistics: sampling, estimation, confidence intervals
  • Probability and hypothesis testing: p-values and significance
  • Regression analysis: linear and logistic regression for prediction
  • Applying statistical methods to real business datasets
  • Python essentials: variables, data structures, functions, loops
  • Pandas: loading, cleaning, filtering, transforming, merging data
  • Exploratory data analysis: profiling datasets and finding patterns
  • Data visualization with Matplotlib and Seaborn
  • Building reusable data pipelines and automation scripts
Project

Python data processing pipeline and exploratory data analysis report.

  • Supervised vs unsupervised learning explained
  • Core algorithms: linear and logistic regression, decision trees, k-means
  • Model evaluation: accuracy, precision, recall, F1, confusion matrices
  • Overfitting, underfitting, and model tuning basics
  • Building and evaluating a predictive model on a business dataset
Project

A machine learning predictive model with full evaluation.

  • How LLMs work: tokens, temperature, and hallucination
  • The connection between generative AI and earlier ML workflows
  • Prompt engineering for extraction, classification, summarization
  • AI for business automation: content, reports, data interpretation
  • Using Claude and ChatGPT as operational co-workers
Project

AI workflow automation: an n8n pipeline or Claude Code workflow.

  • Building a data portfolio to present to employers
  • Resume and LinkedIn optimization for data roles
  • Interview preparation: technical and behavioral questions
  • Job search strategy: where to look, how to apply, how to follow up
  • Capstone presentation coaching for a stakeholder audience
Project

Final stakeholder presentation: a data story from raw data to recommendations.

Your portfolio

Graduate with real projects, not just a certificate

Employers hire what they can see. Every module ships a working artifact you can demo in interviews.

INT1
Data integration workflow
SQL1
SQL data cleaning & analytics
PY1
Python pipeline & EDA report
ML1
Machine learning model
AI1
AI workflow automation
CP1
Final stakeholder presentation
Faculty

Learn from active AI builders

Not academics, but founders and engineers who deploy production AI systems today.

SW
Co-Founder & CEO, Lid Vizion AI
Shawn Wilborne
Lead AI & Data Science Instructor

Startup founder and AI systems builder spanning law, real estate, operations, and AI product development. Collaborated with the University of Miami on computer vision research.

LG
Co-Founder & CTO, Lid Vizion AI
Lamar Giggetts
Lead Technical Instructor

Technical builder focused on AI systems, automation, and workflow architecture, working across APIs, databases, deployment, AI agents, and orchestration.

What students say

Real people. Real outcomes.

Before this program I was doing more manual work with less automation. The instructors go above and beyond. To anyone on the fence: you have nothing to lose. The worst outcome is that you learn something new.
Kevin FragaMiami · Venture Miami Scholarship Recipient
I chose this Academy for the focus on hands-on projects. The AI integration in data science was one of the most interesting parts. If you have curiosity and a desire to learn, don't hesitate.
Armend HoxhaBusiness Analyst, Prishtina · Student of the Month
The practical approach and the combination of data analysis with AI is what drew me in. Statistics and data visualization impressed me most. Data Science is a very valuable skill for the future.
Samire SadikuHigher Education Professional · Student of the Month
Tuition

Choose your track

Pick the learning path that fits your goals. Every track includes the full curriculum and portfolio projects.

Self-Paced Track
Watch recordings on your own schedule with full access to all materials.
€1,499
Local Certificate of Completion
  • All 11 courses and materials
  • 6 real portfolio projects
  • Weekly office hours access
  • Learn at your own pace
Reserve Your Spot
Risk-free preview

Not sure yet? Try a free introductory class

Experience the program's hands-on style before you commit. Learn the basics of Python, SQL, and data pipelines and see if data science is right for you. No experience needed.

Reserve a free seat
FAQ

Common questions

Yes. Live Track graduates with at least 80% attendance earn a U.S.-recognized diploma from Creative Hub Miami that stands out on any CV or LinkedIn profile.

No. The program starts from zero: your first Python variable through to a production-grade data platform.

Six of the 11 courses are taught by Lid Vizion AI, an active Miami AI studio with 12 live production deployments. The rest are taught by Creative Hub faculty.

Live Track students join real-time sessions with U.S. instructors and earn a U.S. diploma. Self-Paced students watch recordings, keep office-hours access, and earn a local certificate.

Yes. Flexible monthly payment plans are available. Write to our coordinator for details.

Not sure yet?

Get a free introductory class

Talk to our coordinator, experience the program's hands-on style, and get clear answers before you enroll. Write to us at [email protected] and we'll set up a free intro session.

CH
Creative Hub Miami Program coordination team
Final step

Ready to build data & AI systems?

The next cohort starts September 5, 2026. Seats are limited to keep every session live and hands-on.

  • Free consultation call, no obligation
  • Flexible monthly payment plans available
  • Applications reviewed on a rolling basis
  • We'll reply within one business day

Reserve your spot

Spots are limited to keep every session live and hands-on. Send your details and we'll be in touch.

Reserve Your Spot

Or email [email protected]