Data Analytics & AI-Assisted Computing Bootcamp

Become a professional data analyst. Master Python, SQL, visualization, and AI-powered analysis. Turn data into insights and launch your analytics career.

12 Weeks - Hands-On - Project-Driven - AI-Powered

available

Advanced Level

Course Instructors

Eteng Eteng

Lead Instructor

John Wilson

Backend Expert

Vivian Effong

Frontend Specialist

What You'll Learn

Analyze real-world datasets using Python and SQL

Clean, transform, and visualize data professionally

Build dashboards and analytics reports

Apply statistics and machine learning for insights

Turn raw data into business intelligence

Use Git and GitHub for version control and collaboration

Integrate databases, code, and visualizations into analytics systems

Present insights clearly to stakeholders

Use AI tools to generate, debug, refactor, and optimize analytics code professionally

Work faster using modern AI-assisted analytics workflows

Preview this course

₦300,000

Enroll Now

This course includes:

12 weeks intensive training
50+ video lessons
5+ Real-world projects
Certificate of completion
Career support & mentorship
Lifetime community access
Live Q&A sessions
Full lifetime access

Course Description

This immersive Data Analytics & AI-Assisted Computing Bootcamp is designed to take you from a beginner to a job-ready data analyst in just 12 weeks. You'll learn by working with real datasets using Python, SQL, visualization tools, and machine learning techniques, while following professional workflows with Git, GitHub, and modern AI-assisted analytics tools. The course emphasizes hands-on learning, real-world projects, and best practices used by modern data teams. Students are trained to use AI responsibly for data cleaning, exploration, modeling, visualization, documentation, and faster problem-solving - exactly how modern analytics and AI teams work today. By the end of the program, you won't just understand data - you'll have a strong analytics portfolio, real project experience, and the confidence to apply for data analyst roles, business intelligence positions, freelance analytics, or build your own data-driven products.

Requirements

A computer with internet connection (Windows, Mac, or Linux)

Basic understanding of how websites work (helpful but not required)

Passion to learn and build amazing web applications

Commitment of 10-15 hours per week for 12 weeks

Course Curriculum

5 comprehensive modules

Data Fundamentals & Python Basics

Weeks 1-2 - 8 Lessons

Introduction to Data Analytics & Career Paths

Understanding Data Types & Structures

Python Basics for Data Analysis

Working with Jupyter Notebooks

Data Cleaning Fundamentals

Introduction to NumPy & pandas

Introduction to Git & Version Control

Using GitHub for Data Project Management

Data Wrangling, Visualization & AI Tools

Weeks 3-5 - 12 Lessons

Advanced pandas for Data Manipulation

Handling Missing, Noisy & Duplicate Data

Data Transformation Techniques

Exploratory Data Analysis (EDA)

Data Visualization with Matplotlib & Seaborn

Creating Interactive Charts & Dashboards

Storytelling with Data

Using SQL for Data Exploration

Structuring Analytics Projects

GitHub Workflow & AI-Assisted Data Analysis

Using AI Tools for Data Cleaning & Insight Generation

Debugging and Optimizing Analysis Code with AI Assistance

SQL, Databases & Applied Analytics

Weeks 6-8 - 10 Lessons

Introduction to Databases & SQL Concepts

Writing Basic & Advanced SQL Queries

Joins, Subqueries & Indexing

Connecting Python to Databases

Data Modeling for Analytics

Working with Real-World Datasets

Statistical Analysis Basics

Hypothesis Testing Fundamentals

GitHub Collaboration & AI-Assisted Query Design

Designing Queries Faster Using AI Tools

Testing and Optimizing Analytics Pipelines with AI Support

Machine Learning & Intelligent Analytics

Weeks 9-11 - 10 Lessons

Introduction to Machine Learning Concepts

Supervised vs Unsupervised Learning

Data Preparation for ML Models

Regression, Classification & Clustering

Model Evaluation Techniques

Feature Engineering Basics

Using scikit-learn for ML Projects

Integrating ML into Analytics Workflows

Full Analytics Collaboration Using GitHub

Using AI to Improve Models, Accuracy & Performance

Deployment, Reporting & Capstone Project

Week 12 - 6 Lessons

Presenting Data Insights Professionally

Building Reports & Dashboards

Exporting & Sharing Analytics Results

Automating Data Pipelines

Managing Live Analytics Projects with GitHub & AI Productivity Tools

Using AI for Documentation, Testing & Report Generation

Optimizing Analytics Systems with AI Suggestions

Best Practices for Maintaining Analytics Solutions

Student Reviews

John Wilson

2 weeks ago

"The best decision I made for my career. The project-based learning approach helped me understand complex concepts easily. Highly recommended!"

Vivian Effong

1 month ago

"Excellent curriculum and amazing support from the instructors. I landed my first developer job just 2 weeks after graduating!"

Frequently Asked Questions

Do I need any prior programming experience?

No prior programming experience is required. This course is designed for complete beginners and takes you from the basics to advanced full stack development.

What happens if I miss a live session?

All live sessions are recorded and made available to you within 24 hours. You'll have lifetime access to all course materials and recordings.

Will I receive a certificate upon completion?

Yes! Upon successful completion of the course and final project, you'll receive a verified certificate of completion that you can share on LinkedIn and your resume.

Do you offer job placement assistance?

Yes! We provide career support including resume reviews, interview preparation, and connections to our network of hiring partners.

What if I'm not satisfied with the course?

We offer a 30-day money-back guarantee. If you're not satisfied with the course within the first 30 days, we'll provide a full refund, no questions asked.

Preview this course

₦300,000

Enroll Now

This course includes:

12 weeks intensive training
50+ video lessons
5+ Real-world projects
Certificate of completion
Career support & mentorship
Lifetime community access
Live Q&A sessions
Full lifetime access