Three-days training programme for young professionals and enthusiasts on data-driven audience segmentation, GenAI-powered strategy building, and no-code analytics.
ENROL NOWApplied Data Science in Advertising is a three-day immersive workshop that takes you from raw social-listening data to deployable ad campaigns and persuasive data stories. You’ll start by loading social-listening feeds into Python, mapping digital tribes with networkx and uncovering sentiment spikes with TextBlob/NLTK - then switch into prompt-driven GenAI to spin up and refine strategic campaign concepts. Next, you’ll compute and forecast campaign metrics (CTR, CPC) in pandas/scikit-learn, design layered microtargeting segments and viral-loop experiments, and build dynamic dashboards in Apache Superset or plotly. The course culminates in a team-led showcase where you merge quantitative KPIs with qualitative ethnographic insights to deliver concise, ethically grounded data-story pitches - and walk away with live prototypes and performance dashboards ready for real-world deployment.
ENROL NOWYou only need to bring a laptop, internet access, and basic comfort operating web applications. No prior experience with advertising platforms or coding is required.
Training will be held on-premise, at Acme AI's production HQ located at Level 4, House 385, Road 6, Avenue 3, Mirpur DOHS, Dhaka 1216, Bangladesh. Session duration per day vary between 4-5 hours. Maximum size of each batch is 15 members to ensure one-to-one mentoring and to cultivate rich engagement.
Tahir is the innovation and UX Lead of Bosch Home Comfort Group in Germany. Beyond being a design and innovation supremacist, he led insights and qualitative research cells at the British Council, Kantar, and the Nielsen Company.
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Shahir was the youngest regional head of sales in Banglalink - a major telecommunication outfit in Bangladesh and an arm of VEON. His engagements span the FMCG and Telecom sectors of Bangladesh, sporting big names such as Robi, Airtel, and Unilever.
LinkedIn
Sadhli founded Acme AI and is a creative technologist who works to democratise and monetise frontier technology skills and knowledge. He engaged with high stakes brands to steward data-driven solutions in advertising and communications - with portfolios ranging in both commercial and causal spheres across South Asia.
LinkedInThe course is structured in a moduled curricula enabling learning to progressively unlock practical skills in data science. The training is held for 03 calendar days. Descriptions of each module and subsequent learning outcomes are:
Participants kick off with a hands-on Python Lab, loading real social-listening datasets into Jupyter, using pandas to compute top hashtags and matplotlib to visualise trends. You’ll then dive into digital ethnography by scripting JSON comment streams to extract user handles, keywords, and timestamps, and rendering interaction networks with networkx. After a brief break, you’ll apply sentiment analysis via TextBlob or NLTK to plot emotional spikes over time, before switching gears into Generative AI for Rapid Ad Strategy - prompt-engineering ChatGPT to spin up multiple campaign frameworks. The day closes with a team workshop where you combine ethnographic insights and AI outputs to generate two distinct GenAI-driven campaign outlines and present them for peer feedback, leaving you with both analytical foundations and creative prototypes.
Participants will learn to ingest and explore social-listening data in Jupyter using pandas and matplotlib, apply sentiment analysis (TextBlob/NLTK) to uncover community moods, and combine those ethnographic insights with prompt-driven GenAI (ChatGPT) to rapidly prototype and refine two strategic ad-campaign outlines.
You begin with a Python Lab on campaign metrics and modeling, loading sample ad metrics into pandas to calculate CTR and CPC and running a simple scikit-learn regression to forecast clicks from spend. Next, you’ll architect layered audience segments, leverage look-alike logic, and plan amplification loops to extend your reach. After a break, you’ll blend your Python results with an open-source dashboard - using Apache Superset or plotly - to build interactive visualisations that fuse quantitative KPIs with qualitative sentiment data. You’ll then tackle ethics, privacy & ad fraud through mini case studies, drafting consent checklists and fraud-detection guardrails. A tutorial on data visualisation will be organised which will need to be replicated in a data storytelling showcase by applicants, in teams, in the following day.
You’ll compute core ad metrics (CTR, CPC) and build a simple predictive model in pandas/scikit-learn, architect layered microtargeting and algorithmic amplification loops, and integrate your quantitative and qualitative findings into an interactive dashboard (Superset or plotly).
Finally, in the team workshop, you’ll refine a mixed-data dashboard and deliver a concise “data-story” pitch, ensuring you leave with a deployable performance dashboard and the narrative skills to drive buy-ins from internal stakeholders and clients.
Craft a concise, ethically grounded data-story pitch for stakeholders.
In order to be certified, enrollees must complete all assignments and quizzes in satisfaction - ending with development of a cohesive spatial informatic portfolio for external demonstration.
Assignments include developing siloed spatial system components and outputs - both individually and as a group.
Quizzes are MCQs organised in-class surrounding course curriculum, in addition to national and global industry lore in spatial informatics.
The most important takeaway from this course is the development of a spatial informatics portfolio document for securing earning avenues.
Formal tuition for the course and scholarship details are as followed:
The tuition fee covers 5-days training, 3-4 hrs. each day, logistics and venue costs, tea-break and food. You will be invited to pay the course fee upon completing registration for the course.
Scholarships, if opted for in the registration form, are awarded based on merit of the candidate and quality of responses on the scholarship section in the enrolment/registration form.
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3D ray-traced density maps based on dataset.
Land Use and Land Cover temporal comparison.
Urban Building Segmentation using predictive algorithms.
Street mapping and nav-point visualisation.
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Due to high volume of application, we allocate seats at a first-come-first-serve basis. Please fill out the application form and make payments at your earliest convenience to be in que for enrolment in our training programmes.
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