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into your own hands.
This course gives you a deep dive into the art and technical skills behind
professional-grade photo editing. Starting with the fundamentals of image formats,
resolution, and colour management, you'll build from basic corrections to advanced
compositing. You'll learn how to use tools like Adobe Photoshop (or similar) for
retouching portraits, removing blemishes, adjusting tones, and working with layers
and masks. The course also covers creative manipulation—combining different
elements, working with filters, and using blend modes to create surreal or stylistic
images. You’ll master non-destructive workflows, so your original image is always
preserved, and learn to work efficiently with adjustment layers and smart objects.
There are guided hands-on projects (for example, restoring old photos, creating
digital collages, or editing a professional portrait). By the end, you'll
produce a portfolio of edited images that showcase a range of skills. The course is
suitable both for beginners who want to level up and for hobbyists aiming to do
photo editing commercially.
This course takes you on a journey from the basics of video editing to advanced
storytelling through video. You start by understanding how to import and organize
media, set up your editing workspace, and cut footage with precision. You’ll learn
transitions, pacing, and how to build a narrative emotionally and rhythmically. The
course also delves into colour correction and grading, teaching you how to
manipulate exposure, contrast, and colour to give your video a cinematic feel. Audio
is another critical module: you’ll learn to clean up dialogue, mix sound effects,
background music, and voice-over to make your final output sound professional. Next,
you explore motion graphics and visual effects (VFX), using tools like After Effects
(or similar) to create lower thirds, animated titles, and effects. You will also
dive into rendering and exporting, understanding codecs, and delivery formats for
web, broadcast, or social media. Hands-on project work ensures that by the end
of the course, you’ve built real-world pieces: short films, content reels, or
promotional videos. Finally, you’ll learn efficient workflows and backup strategies
to make your editing process smoother and more
reliable.
This course equips you with the foundational design principles that every designer
needs to know. You begin with visual communication theory: understanding how form,
shape, and space convey meaning. You’ll study colour theory, learning about harmony,
contrast, and how to use colour palettes effectively. Typography is another core
component — you’ll learn about font selection, pairing, hierarchy, and readability.
You will also dive into layout and composition, using grids, alignment, and balance
to structure your designs. The course then introduces branding basics: creating
logos, working with icons, and designing for different formats (print, web, social).
Tools are covered too: you learn how to apply these principles using design software
like Adobe Illustrator, InDesign, or free equivalents. Practical assignments let
you apply each module’s theory: mood boards, branding elements, poster designs,
maybe a small brochure or social media asset pack. By the end of the course, you
will have built a mini portfolio and can confidently communicate your design
decisions.
This masterclass is designed to make you interview-ready by covering all stages of
the process. You’ll begin with mental preparation: managing nerves, building
confidence, and crafting your personal pitch. The next module helps you analyse the
job description, research the company, and tailor your answers so they align with
the employer’s needs. Then you move into common and tricky interview questions:
behavioural (STAR method), technical, strengths & weaknesses, and salary
negotiations. There's a dedicated part on virtual interviews — how to present
yourself via Zoom, good lighting, camera setup, and body language. You’ll also learn
how to ask strategic questions at the end of the interview that demonstrate insight
and interest. After the interview, the course covers follow-up etiquette,
thank-you emails, and how to learn from feedback. Throughout, there are
mock-interview exercises, self-assessment tasks, and downloadable worksheets (e.g.,
question bank, self-pitch templates). By the end, you will feel more prepared,
composed, and able to articulate your value
confidently.
This course walks you through interior design from first principles to finished
concepts, on a room-by-room basis. You start with design principles (balance,
harmony, scale) and space planning: understanding how to zone a room, work with
circulation, and place furniture. Next, you learn about materials: flooring, wall
finishes, and textiles, and how to choose them for aesthetics and
functionality. Colour schemes and lighting are covered, teaching you how to
create mood with light and coordinate colours across a space. Then you move into
soft furnishings, window treatments, and accessories — how to pick and style these
to bring personality into a room. You’ll also explore the practical side of
designing kitchens, bathrooms, living rooms, and bedrooms: workflow, ergonomics, and
storage solutions. A hands-on design project asks you to design one room, applying
everything you’ve learned. Throughout the course, you will use mood boards,
sketches, and optionally design software to visualise and refine your ideas. By the
end, you’ll not only understand interior design theory, but you’ll have a tangible
design proposal you can share or use as
inspiration.
This bootcamp is tailored for beginners but paced to give you real-world,
job-relevant data science skills. You start by learning Python (or R) and the
libraries commonly used in data science (Pandas, NumPy, Matplotlib). Then you’ll
move into data cleaning and wrangling — how to handle missing data, outliers, and
prepare datasets for analysis. The next phase is exploratory data analysis
(EDA), where you visualise distributions, correlations, and identify trends or
anomalies. You’ll then tackle the statistics foundation: probability, hypothesis
testing, and confidence intervals, which are essential for making data-driven
conclusions. After that, you’ll learn machine learning basics: linear regression,
classification, clustering, and model evaluation. The course also covers more
advanced techniques (if time): decision trees, ensemble methods, or neural networks.
Importantly, you’ll learn how to communicate data: build dashboards, visual reports,
and tell a story with data to stakeholders. There are practical projects (e.g.,
predicting outcomes, exploratory dashboards) and a final capstone where you apply
everything to a real or synthetic dataset. Upon completion, you’ll have a portfolio
piece and enough understanding to dive into data science roles or further
specialization.
Modules Introduction to Python
& Data Science Ecosystem — 6 hours Data Cleaning &
Preprocessing — 5 hours Exploratory Data Analysis (EDA) — 5
hours Statistics & Probability for Data Science — 6 hours Introduction
to Machine Learning — 7 hours Advanced ML Techniques (Optional) —
6 hours Data Visualization & Storytelling — 4 hours Capstone
Project — 8 hours
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