Applied AI/ML Career Track
Practical AI/ML skills designed for career growth — guided live sessions, real-world use cases and projects that show what you can do, not just what you watched.
- Live Cohort-Based Training
- Practical Learning
- Placement Assistance
- No Post-Placement Fee
- Category
- Artificial Intelligence • Machine Learning
- Duration
- 40 Days
- Learning format
- Live Online • Cohort-Based
- Level
- Beginner-friendly
- Upcoming batch
- New batch — starts 11 September 2026
Course fee
Includes live sessions, assignments and career support.
Duration
40 Days
Format
Live Online
Learning
Cohort-Based
Support
Placement Assistance
Certificate
Course Certificate
Build skills you can actually use.
This is an applied track, not a research programme. The focus is on understanding how AI and machine learning are used in real work, and being able to build and explain something yourself.
Understand practical AI/ML concepts
Learn what models actually do, where they fit and how teams use them — without getting lost in heavy mathematics.
Work with real-world use cases
Examples drawn from analytics, operations and content workflows rather than toy textbook datasets.
Build career-ready technical knowledge
Python, data handling, modelling and evaluation — the foundation entry-level AI and data roles ask for.
Learn through guided projects and live sessions
Every concept is applied in a guided exercise, with doubt support during the cohort.
What you’ll learn
The outcomes below reflect exactly what the 40-day programme covers. It builds solid, applied fundamentals — it does not claim to make you a research-level ML specialist in six weeks.
- Artificial Intelligence fundamentals
- Machine Learning fundamentals
- Supervised and unsupervised learning
- Data preparation
- Feature engineering
- Model training concepts
- Model evaluation
- Practical AI/ML use cases
- Generative AI fundamentals
- AI tools and workflows
- Real-world project applications
- Career-oriented AI/ML skills
Course Curriculum
Structured learning from fundamentals to practical application.
01Introduction to AI & Machine Learning
What AI and ML are, and where each is actually used.
- AI vs ML vs deep learning
- Types of ML problems
- The end-to-end ML lifecycle
- Common industry use cases
02Python & Data Fundamentals
The programming and statistics base you need before modelling.
- Python syntax and data structures
- pandas and NumPy basics
- Descriptive statistics
- Working with files and datasets
03Data Preparation & Exploration
Most of the real work: getting data into usable shape.
- Cleaning and handling missing values
- Exploratory data analysis
- Visualisation for insight
- Feature engineering basics
04Supervised Learning
Prediction and classification with labelled data.
- Linear and logistic regression
- Decision trees and ensembles
- Train/test splits
- Hands-on model building
05Unsupervised Learning
Finding structure when there are no labels.
- Clustering approaches
- Segmentation use cases
- Dimensionality reduction basics
- Interpreting cluster output
06Model Evaluation & Optimization
Knowing whether a model is actually any good.
- Accuracy, precision, recall, F1
- Cross-validation
- Overfitting and underfitting
- Basic hyperparameter tuning
07Practical Machine Learning Workflows
Putting the pieces together as a repeatable process.
- Structuring an ML project
- Reusable notebooks and code hygiene
- Version control basics
- Communicating results
08Generative AI Fundamentals
How modern generative models work at a practical level.
- Large language model basics
- Prompting fundamentals
- Strengths and limitations
- Responsible use considerations
09AI Tools & Real-World Applications
Applying AI tooling to everyday work.
- Working with pretrained models and APIs
- Automating analysis tasks
- Use cases across business functions
- Choosing the right tool for a problem
10Capstone Project & Career Preparation
Ship something you can show, then get ready to apply.
- End-to-end capstone build
- Project presentation and review
- Resume and profile guidance
- Interview preparation
Learn by doing.
You apply each concept while the cohort runs — assignments, guided exercises and a capstone project that becomes portfolio evidence of what you can do.
Data Projects
Take a raw dataset through cleaning, exploration and insight with mentor feedback.
Machine Learning Models
Train, evaluate and improve models on real problems rather than pre-solved examples.
AI/ML Applications
Use AI tools and pretrained models to build something useful end to end.
Where can these skills take you?
These are the entry-level roles this training is designed to prepare you for.
- Junior AI/ML Analyst
- Machine Learning Intern
- Data/AI Analyst
- AI Operations Associate
- Junior ML Engineer
- AI Automation Associate
Career outcomes depend on individual skills, experience, performance and hiring conditions. The D’s Academy provides placement assistance but does not guarantee employment.
Career Support Beyond the Classroom
The D’s Academy supports students in preparing for the hiring process after completing their training.
Resume Building
Structure a compliance- or data-ready CV with the keywords recruiters and screening tools actually look for.
LinkedIn Profile Optimization
Headline, About section and skills reworked so recruiters can find and shortlist you.
Naukri Profile Setup
Complete profile setup and refresh guidance so your application reaches the right job listings.
HR Contacts & Job Support
Shared openings, referral pointers and interview preparation support through your job search.
No post-placement fee
Who should join
- Students
- Fresh graduates
- Working professionals
- Career switchers
- Non-coding professionals interested in AI
- Entrepreneurs wanting practical AI skills
How the programme runs
- Duration
- 40 Days
- Mode
- Live Online
- Learning
- Cohort-Based
- Sessions
- Live instructor-led sessions with recordings
- Support
- Assignments + Doubt Support + Career Preparation
- Certificate
- Course Certificate
Who teaches this programme
The D’s Academy Faculty
AI & Data Training Team
Instructor profile to be published
Sessions are delivered by The D’s Academy AI and data training team. Detailed instructor credentials will be published here before the batch begins — ask us and we will share them directly.
Questions, answered
Is this course live or recorded?
Sessions are live and instructor-led, with recordings shared for revision.
Will I receive a certificate?
Yes — a course completion certificate is issued after the capstone project.
Do you charge any post-placement fee?
No. The D’s Academy does not charge a post-placement fee.
Who can join the course?
Students, graduates, working professionals and career switchers, including non-coders who want practical AI skills.
How do I enroll?
Use Enroll Now to open the registration form and our team will confirm your seat and batch details.
How long is the course?
40 days of structured, cohort-based training.
Is placement guaranteed?
No. The D’s Academy provides placement assistance, but employment is not guaranteed.
What kind of placement assistance is provided?
Resume building, LinkedIn and Naukri profile optimisation, interview preparation, and support with HR contacts and shared job openings.
Is prior experience required?
No. Python and data fundamentals are taught from the beginning before any modelling work.
Next cohort: 11 September 2026
Ready to build career-ready skills?
Join the next cohort and start building practical skills with The D’s Academy.
₹15,000
New batch — starts 11 September 2026