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Course Details
Course Details
What You'll Learn
Topic 1: Data Preparation
Topic 2: Data Transformation
Topic 3: Data Visualization
Topic 4: Data Analysis
Topic 5: Advanced Data Analytics
Course Info
Prerequisite
Basic computer and file-management skills are expected. Familiarity with basic programming, data handling and elementary statistics will help you follow the exercises.
Software Requirement
Install and test the listed software before class. Confirm the required version and account or licence access in your joining instructions. Cloud and AI services may charge subscription or usage fees.
Also prepare the tools needed for the practical exercises:
Confirm the version, account permissions and any API usage budget with the trainer before class.
Hardware Requirement
Bring a Windows or Mac laptop supported by the listed software, with a working keyboard and sufficient storage for course exercises.
Bring your own computer and charger, with a reliable internet connection and permission to install the required software. For live online classes, also prepare a microphone or headset.
If you need help arranging a suitable device, contact us before the class to confirm availability.
Job Roles
Job Roles
- Aspiring Software Developer
- Data Analyst
- Web Developer
- Automation Engineer
- Data Scientist
- System Administrator
- Bioinformatics Specialist
- Research Scientist
- Finance Professional
- Machine Learning Enthusiast
- GIS (Geographic Information System) Specialist
- IT Consultant
- Network Engineer
- Database Administrator
- Tech Entrepreneur.
Trainers
Trainers
Dr. Muhammed Siraj is a cybersecurity specialist and academic with 15 years of experience, serving as Senior Lecturer in the Department of Informatics and Director of Graduate and Continuous Education at Academic City University in Accra. He holds a PhD in Security in Computing from Universiti Putra Malaysia, where his research focused on blockchain security, an MSc in Information and Communication Technology from Aalborg University in Denmark, and a degree from the University of Ghana. He is a licensed independent assessor with Ghana's Cyber Security Authority, holds leadership roles in national cybersecurity and privacy professional bodies, and is certified as a Certified Ethical Hacker (CEH), Computer Hacking Forensic Investigator (CHFI) and Certified Data Protection Supervisor (CDPS). Before joining Academic City, he served as Acting Director of ICT and Data Protection Supervisor at Wisconsin International University College. His expertise spans penetration testing, digital forensics, incident response, malware analysis, cryptography, cloud and IoT security, zero trust architecture, cyber threat intelligence, data protection, and governance, risk and compliance.
Dr. Siraj's research interests cover blockchain, cybersecurity, distributed computing, consensus protocols and machine learning, with published work on blockchain consensus security, smart-contract privacy preservation for sensitive records in the cloud, and new consensus mechanisms. This background gives him a distinctive perspective on artificial intelligence: as organisations adopt AI tools, agents and data-driven automation, he helps learners understand how to protect the data these systems depend on, recognise new attack surfaces, and put sound governance, privacy and access controls in place so that AI can be used safely and responsibly. In the classroom he connects technical practice with regulation, privacy and human factors, drawing on real-world security and data-protection cases to show how concepts apply in professional settings, and his experiential, hands-on teaching style has made him a trusted trainer for students and working professionals alike.
Spreadsheets of enrolments, stock levels and market prices are everyday material for Dr. Alfred Ang, a full-stack AI developer and Agentic AI solution architect who serves as CTO of Tertiary Infotech Academy Pte Ltd in Singapore, the training organisation behind Tertiary Courses. Alongside corporate training, Dr. Ang builds intelligent agents and business systems end-to-end, from front end and back end to databases, cloud deployment and native mobile apps, and shares the work through more than 300 public repositories on GitHub. Python data work runs through many of them. A set of interactive Python and Streamlit labs teaches beginners data mining and machine learning with live, adjustable examples. A stock-analysis dashboard charts live price and volume data and connects to a Telegram AI agent that explains its buy, sell or hold calls. An inventory audit and forecasting agent on n8n uses a local language model to flag items below reorder thresholds, calculate replenishment and report through Google Sheets and Gmail. Several Streamlit applications built with the Claude Agent SDK turn structured course information into finished training documents automatically, showing how analysis and generation can be combined in a single tool. Dr. Ang also maintains the course-registration platform behind the Tertiary Courses sites in Singapore, Malaysia and Ghana, whose registration and catalogue data regularly needs to be exported, cleaned, joined and summarised. In nearly every case the first draft of the code came from an AI coding assistant, and the real skill lay in prompting precisely and checking the output against the data.
That is the skill this course develops. The first topic explains what AI vibe coding is, sets up Cursor, GitHub Copilot and Claude for data analysis, and teaches prompting patterns that produce correct pandas code rather than plausible-looking errors. Learners then import and export data with AI assistance, clean, filter and slice it, and join, transform and aggregate tables, the steps where most real-world analysis time is spent. The second topic turns to insight: generating charts with Matplotlib and Seaborn from prompts, visualising relationships, categories and correlations, carrying out statistical analysis with AI help, and reading trends in time series. Dr. Ang shows how to iterate on an analysis through follow-up prompts, refining a chart or a calculation step by step instead of starting over, and the course closes with summarising findings into a shareable report. Throughout, learners are taught to sanity-check results, for example by recounting rows after a join or comparing a total against the source, habits Dr. Ang relies on when stock or registration numbers feed real decisions. Sessions are hands-on, built around realistic datasets, and paced so that people with little Python experience can keep up while more experienced analysts pick up faster workflows. Participants leave with reusable notebooks, polished charts and the confidence to direct an AI assistant through a full analysis. To explore the data labs and dashboards that inform this course, visit Dr. Ang's portfolio at https://github.com/alfredang
Review
Customer Reviews (8)
- Hands-on and practical Review by Course Participant/Trainee
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A very practical course. The trainer made a complex topic simple and enjoyable to learn. (Posted on 1/7/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Knowledgeable trainer Review by Course Participant/Trainee
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Very informative and interactive. The small class size meant we got a lot of personal attention. (Posted on 1/7/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Excellent course Review by Course Participant/Trainee
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Well organised course with clear objectives. The step-by-step approach made it easy to follow. (Posted on 12/7/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Very informative Review by Course Participant/Trainee
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Solid content and a supportive trainer. I would definitely sign up for more courses here. (Posted on 4/5/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Very informative Review by Course Participant/Trainee
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The trainer is an expert in the subject and shared many practical insights from real projects. (Posted on 11/13/2024)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
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