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Certificate in AI Data Intelligence and Business Analytics

Collect, analyze, visualize, and interpret data to support intelligent business and engineering decision-making using AI-powered analytics tools.

Last updated 07/2026EnglishBeginner to Intermediate

About this programme

Collect, analyze, visualize, and interpret data to support intelligent business and engineering decision-making using AI-powered analytics tools.

Delivered as 60 live two-hour sessions across 8 modules, with a graded build at the end of every module and a mentor-reviewed capstone to finish.

Course outcomes

What you will be able to do on completion

This programme is built around capability, not coverage. By the end you will be able to:

01Collect and combine data from databases, files and APIs
02Clean and model messy real-world data into an analysable shape
03Write SQL confident enough for production analytics work
04Build dashboards people actually use to make decisions
05Apply AI-powered analytics for forecasting and segmentation
06Use natural-language analytics tools without being misled by them
07Communicate findings as a decision, not a chart dump
08Apply data quality and governance practice
09Deliver an analytics project from raw data to recommendation

Course content

8 modules · 60 sessions · 120 hours

Sessions run two hours each, live with an instructor. Each module closes with a graded build.

1.1 The analytics workflow end to endPreview2 hrs

1.2 Data types, structures and sourcesPreview2 hrs

1.3 Spreadsheets to databases2 hrs

1.4 Descriptive statistics that matter2 hrs

1.5 Sampling, bias and common traps2 hrs

1.6 Reading a dataset critically2 hrs

1.7 Analytics tooling landscape2 hrs

1.8 Setting up your analytics workspace2 hrs

2.1 Extracting data from systems and APIs2 hrs

2.2 Handling missing and duplicate data2 hrs

2.3 Outliers and how to treat them2 hrs

2.4 Joining and reshaping datasets2 hrs

2.5 Dimensional modelling basics2 hrs

2.6 Building a clean analytical table2 hrs

2.7 Automating a data preparation pipeline2 hrs

2.8 Documenting data lineage2 hrs

2.9 Version control for analysis2 hrs

2.10 Workshop: cleaning a messy dataset2 hrs

3.1 Querying fundamentals2 hrs

3.2 Joins in practice2 hrs

3.3 Aggregation and grouping2 hrs

3.4 Window functions2 hrs

3.5 Common table expressions2 hrs

3.6 Query performance basics2 hrs

3.7 Analytical query patterns2 hrs

3.8 Build: an analytical query suite2 hrs

4.1 Choosing the right chart2 hrs

4.2 Designing for comparison2 hrs

4.3 Colour, scale and honest axes2 hrs

4.4 Building your first dashboard2 hrs

4.5 Filters, drill-down and interactivity2 hrs

4.6 Dashboard performance2 hrs

4.7 Designing for a specific decision2 hrs

4.8 Accessibility in data visuals2 hrs

4.9 Reviewing and iterating a dashboard2 hrs

4.10 Project: a decision dashboard2 hrs

5.1 Where AI helps in analytics2 hrs

5.2 Natural-language querying of data2 hrs

5.3 Automated insight generation and its limits2 hrs

5.4 Forecasting fundamentals2 hrs

5.5 Time-series forecasting in practice2 hrs

5.6 Segmentation and clustering2 hrs

5.7 Classification for business questions2 hrs

5.8 Explaining model output to stakeholders2 hrs

5.9 Validating AI-generated analysis2 hrs

5.10 Project: an AI-assisted analysis2 hrs

6.1 Structuring an analytical narrative2 hrs

6.2 From finding to recommendation2 hrs

6.3 Presenting uncertainty honestly2 hrs

6.4 Executive summaries that land2 hrs

6.5 Handling challenge and pushback2 hrs

6.6 Workshop: presenting your analysis2 hrs

7.1 Defining and measuring data quality2 hrs

7.2 Testing data pipelines2 hrs

7.3 Privacy and access control2 hrs

7.4 Regulatory basics for analysts2 hrs

7.5 Metric definitions and a single source of truth2 hrs

7.6 Governance in practice2 hrs

8.1 Capstone analysis and mentor review2 hrs

8.2 Portfolio, resume and interview preparation2 hrs

Requirements

A laptop with internet access
Willingness to work through hands-on builds each module
No prior AI background required — the first module starts from fundamentals
Around four hours a week outside sessions for project work

Description

Collect, analyze, visualize, and interpret data to support intelligent business and engineering decision-making using AI-powered analytics tools.
60 live sessions across 8 modules, 120 hours in total.
Every module closes with a graded build reviewed by a mentor.
Finish with a verifiable certificate recognised by our hiring partners.

Instructor

Dr. Neha Rao

Lead AI Instructor · TEVVO Academy

12,480 reviews41,200 students9 courses

Neha has spent a decade building machine learning systems in production, most recently leading an applied AI team. She teaches the way she works — starting from a real problem, then building the smallest thing that solves it.

Student feedback

4.9Course rating

78%

14%

Featured reviews

Ananya S.

Structured, practical and paced properly. The graded build at the end of each module is what made it stick.

Karthik R.

The mentor reviews were the most valuable part — real feedback on real work, not just a quiz score.

Meera J.

Genuinely current material and a sensible schedule alongside a full-time job.