SoftPro9 runs Data Science with Machine Learning & AI training as live online batches in Oman time, for learners in Sohar, Salalah, Nizwa, Sur, Duqm and Muscat.
Last updated: 28 October 2026
Port, logistics and plant data in Sohar, Salalah and Duqm suit forecasting and maintenance models. The course is split into three levels. You can join at the level that matches your experience after a short assessment at counselling.
Oman practice: 5% Oman VAT in invoice data.
Oman practice: Arabic text and right-to-left (RTL) layouts.
Oman practice: Seasonal tourism patterns such as Salalah's khareef season.
Freshers usually start in junior or support versions of these roles.
Data Science with Machine Learning & AI – full course details and fee →
Every tool below is used hands-on in class or in a project, not just mentioned on a slide.
A customer-churn model with feature engineering, explainability and a business write-up
A demand-forecasting model compared against a simple baseline
A document question-answering assistant built with RAG and evaluated on real questions
A capstone deployed as an API and Streamlit app, with experiment tracking in MLflow
Oman project: A forecast of container volumes at a port, using data and conventions from Oman.
New batches start every Monday and Thursday, with no more than 15 learners in each. Weekday class slots in GST (Oman): 8:30 AM / 7:30 PM / 10 PM. Weekend slots: 9 AM / 9 PM.
Rotation workers join live during off weeks and use recordings on site; weekend batches suit plant staff.
| Start date | Course | Mode | Batch size |
|---|---|---|---|
| Thu, 29 Oct 2026 | Data Science (all levels) | Live online | Up to 15 |
| Mon, 2 Nov 2026 | Data Science (all levels) | Live online | Up to 15 |
| Thu, 5 Nov 2026 | Data Science (all levels) | Live online | Up to 15 |
| Mon, 9 Nov 2026 | Data Science (all levels) | Live online | Up to 15 |
Message us with the start date and slot you want, and we will confirm your seat.
Data science uses statistics, programming and machine learning to answer questions and make predictions from data: which customers will churn, how much stock to order, whether a transaction looks fraudulent. A data scientist frames the question, prepares the data, builds and evaluates models, and explains the result to people who will act on it.
The field now overlaps heavily with AI engineering, so alongside classic machine learning (scikit-learn, XGBoost) we cover deep learning with PyTorch, natural language processing with Hugging Face transformers, building on large language models with retrieval-augmented generation (RAG), and the MLOps needed to put a model into production.
The three fields share tools and are often confused in job titles. The simplest way to tell them apart is by the question each one answers.
| Aspect | Data Analytics | Business Analytics | Data Science |
|---|---|---|---|
| Main question | What happened, and why? | What should the business do? | What will happen, and can we automate the decision? |
| Focus | Cleaning data, reporting, dashboards | Turning analysis into business decisions and plans | Predictive models, machine learning and AI |
| Core tools | Excel, SQL, Power BI, Tableau | Excel, SQL, Power BI, forecasting, BRDs and process maps | Python, statistics, scikit-learn, PyTorch, MLOps |
| Maths needed | Basic statistics | Business statistics and forecasting | Statistics, linear algebra and probability |
| Coding | Low (SQL, some Python) | Low (SQL, light Python) | High (Python every day) |
| Typical output | Dashboards and reports | Recommendations, business cases, requirement documents | Models, predictions and AI features |
| Typical first roles | Data analyst, MIS analyst, Power BI developer | Business analyst, BI analyst, strategy analyst | Junior data scientist, ML engineer |
| Best starting point for | Anyone new to data, any degree | MBA, BBA and commerce graduates, managers | Engineering, maths and statistics graduates, developers |
| Course length here | 14–16 weeks | 14–16 weeks | 24–28 weeks |
Which should you choose? If you are new to data, start with Data Analytics: it is the foundation the other two build on. Choose Business Analytics if you enjoy the business side and want to influence decisions. Choose Data Science if you like programming and maths and want to build predictive models.
Outside Muscat, Oman's economy is built around ports and industrial zones: Sohar's port and free zone, Salalah's container port and free zone, and the Duqm special economic zone, plus oil and gas fields in the interior. These operations increasingly depend on data, automation and digital systems.
Ports and free zones
Oil, gas and mining
Manufacturing
Tourism
Generic courses use generic datasets, and interviewers notice. Our exercises include:
| Your background | Start with | Why |
|---|---|---|
| Engineering / maths / statistics graduate | Full course | The maths will feel familiar; the tooling is what you need |
| Data / business analyst | ML modules, then deep learning | You already know SQL and the business; add prediction |
| Software developer | ML basics, then GenAI and MLOps | AI engineering roles value your production skills |
| Commerce / non-technical graduate | Data Analytics first | Build SQL, Excel and statistics before ML |
| Domain expert (finance, healthcare, supply chain) | Full course with a domain capstone | Domain knowledge is what makes models useful |
Common pairings: Data Science + Data Analytics (if you are starting without SQL or statistics), Data Science + Python (if you are new to programming), and Data Science + Web Development (for AI-product roles). Learn one course well before adding a second.
Master the python, maths and data handling before moving on.
Build and publish your projects, including the Oman capstone.
Apply for entry roles such as data scientist or machine-learning engineer with employers like the ports and free zones above.
Honest note: freshers usually start in junior or trainee roles, and salaries in Oman vary too widely for a headline figure. Ask us which openings we are seeing.
Data science has no single official certification. Cloud vendors run optional role exams such as Microsoft Azure Data Scientist Associate (DP-100) and AWS Certified Machine Learning, paid directly to the vendor and not part of our fee; we point out which modules map to them. SoftPro9 issues a course completion certificate. Hiring managers look mainly at your projects and how clearly you explain them.
A 2026 syllabus: look for Streamlit, Docker, PySpark, Databricks, not only the basics.
Projects on your own accounts, a trainer you can meet first, and a published fee with nothing hidden.
No "global certification" or "100% placement" claims: vendors run their own exams, and nobody can promise a job.
Taught from Bangalore
Live, with recordings and reviews
Interview preparation
| Area | Where | Most learners choose |
|---|---|---|
| Sohar, Al Batinah | North | Live online, evening slots |
| Salalah, Dhofar | South | Live online |
| Nizwa, Ibri, interior fields | Interior | Live online, weekend batches suit rotations |
| Sur, Duqm | East coast | Live online |
Oman batches are live online in Oman time, so learners anywhere in the country can join. Muscat learners can also see our Muscat page.
Oman batches are live online. They are run from our Bangalore centre, which you are welcome to visit if you are ever in the city.
SoftPro9 IT Services – Bangalore
22/1, Opp Infosys, BHBCS Layout, BTM Layout 2nd Stage, BTM Layout, Bengaluru, Karnataka – 560076
Phone: +91 95354 51414
We are in BTM Layout 2nd Stage, opposite the Infosys office. The nearest metro is Jayadeva Hospital station, about a 10-minute walk away, and BMTC buses on the Outer Ring Road and Bannerghatta Road stop nearby.
Monday–Friday 9:30 AM–7:30 PM · Saturday 9:30 AM–3:30 PM · Sunday closed
The current training fee is listed on the Data Science with Machine Learning & AI course page: /course/data-science-course. It covers live classes, the practice environment, projects and interview preparation. Any optional cloud ML exam (DP-100, AWS ML) is optional, not included, and paid directly to the exam provider.
You need school-level maths and a willingness to learn. We teach the statistics, linear algebra and calculus ideas ML relies on, with intuition and code rather than proofs.
Yes. You work with LLM APIs, build a retrieval-augmented generation (RAG) assistant, and learn how to evaluate it, alongside classic ML.
Data analytics explains what happened and why, using SQL, Excel and BI tools. Data science predicts what will happen and builds models. If you are new to data, analytics is the easier start.
No. Deep-learning work runs in GPU-enabled cloud notebooks we provide during the course.
Yes. All classes are recorded, and you can attend live during your off-rotation weeks and catch up from recordings when on site.
No. Oman batches are live online in Oman time, with a 15-learner cap.
New Data Science batches start every Monday and Thursday. See the batch table on this page for the next dates and GST (Oman) class slots.
No. We provide interview preparation, resume help and referrals to openings we hear about in Oman, but no institute can honestly guarantee a job.
Tell us your degree, your current job (if any) and where in Oman you are. We will suggest a track and a batch that fits.
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