Master the Foundations of AI and Build Real Projects
Go from Python and mathematical foundations to machine learning, deep learning, Generative AI, RAG, and AI agents through a focused, hands-on learning experience.
An intensive program designed for learners who want to understand AI concepts and apply them in practical projects.
Understand the concept. Learn the math. Build with code.
Learn AI step by step. Start with intuitive explanations, understand the important mathematical ideas, implement them in Python, and apply what you learn to practical problems.
Build Strong Foundations
Develop your understanding of Python, data, mathematics, statistics, and the principles behind AI systems.
Practise with Python
Work with code, datasets, visualizations, and established libraries to turn concepts into working implementations.
Apply AI in Projects
Explore prediction models, document question-answering systems, and AI-assisted workflows.
Designed for aspiring AI builders
The program is suitable for motivated learners ready to practise consistently during an intensive 30-day schedule.
Beginners & Python Learners
Build a foundation in data analysis, machine learning, and modern AI. Basic programming familiarity is helpful.
Developers & Automation Engineers
Expand your skills into ML, LLM applications, retrieval-augmented generation, and AI workflow development.
Working Professionals
Choose a weekday or weekend batch that better suits your existing schedule.
Career Changers
Build practical experience and projects that can support your ongoing learning and portfolio development.
What you will learn
A focused curriculum that progresses from core foundations to machine learning and modern Generative AI applications.
1–3
Python & Data Foundations
Python essentials, functions, NumPy, Pandas, data cleaning, and exploratory data analysis.
4–6
Mathematics for AI
Vectors, matrices, dot products, functions, derivatives, gradients, and optimization concepts.
7–8
Statistics & Probability
Distributions, mean, variance, correlation, probability, sampling, and interpreting data.
9–13
Machine Learning
Regression, classification, clustering, feature engineering, model evaluation, overfitting, and model tuning.
14–17
Deep Learning
Neural networks, weights, activation functions, loss functions, backpropagation, and training intuition.
18–21
Generative AI & LLMs
Large language models, tokens, transformers, prompt engineering, embeddings, and AI application patterns.
22–25
RAG & AI Agents
Document retrieval, vector search, retrieval-augmented generation, tool use, and introductory agent workflows.
26–29
Hands-on Project Development
Combine your skills to develop, test, and document practical data science and AI applications.
30
Final Project & Review
Present your project, review your implementation, discuss limitations, and plan your next learning steps.
Important: This is an intensive 30-day roadmap. Topics may be adjusted to the batch pace, and independent practice will be important for success.
Turn concepts into practical projects
Suggested project work helps learners connect the concepts covered during the program.
Data Analysis & Insights
Clean a dataset, explore trends, visualize patterns, and communicate useful findings.
Machine Learning Prediction
Train a classification or regression model, measure performance, and explain its limitations.
AI Document Assistant
Build a starter document question-answering application using retrieval and an LLM.
AI Workflow Prototype
Create an AI-assisted workflow with tool use, input validation, and appropriate human review.
Two batch options. One learning program.
Select the schedule that best fits your availability when you register.
Monday – Friday
For learners who can dedicate time to training during the working week.
- Monday to Friday schedule
- 30-day intensive program
- Course fee: $1,000 USD
Saturday – Sunday
For working professionals and learners who prefer weekend sessions.
- Saturday and Sunday schedule
- Intensive learning plan across 30 calendar days
- Course fee: $1,000 USD
Batch scheduling: Exact class timings, start dates, session frequency, and any additional practice arrangements will be confirmed by the course team. The weekend batch follows the same 30-calendar-day program timeline.
Before you enrol
Do I need prior AI or machine learning experience?
No prior machine learning experience is required. Basic programming knowledge is helpful. Learners should be prepared for a fast-paced program with regular practice.
How long is the course?
The program is designed to run over 30 calendar days. It is an intensive course covering foundations, machine learning, Generative AI, and project work.
What is the course fee?
The listed course fee is $1,000 USD. Confirm the applicable payment method and any taxes or additional charges with the course team before payment.
What is the difference between the two batches?
The weekday batch is scheduled Monday through Friday. The weekend batch is scheduled for Saturday and Sunday. Exact session timings are confirmed separately.
Will I build projects?
The proposed curriculum includes practical work in data analysis, machine learning, document Q&A, and AI workflows. The exact project scope depends on the batch schedule and learning pace.
Will I receive a job or placement guarantee?
The course page does not promise a job or placement. The program is intended to help learners build skills and practical project experience.
Ready to build your AI skills?
Choose your preferred batch and submit your details using the MyAutomationTime course registration form.
30 days · $1,000 USD · Weekly or Weekend
Complete the registration form below. If the form is not displayed, add your existing registration shortcode to this page as described below.
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