ACCELERATE WITH AI/ML ENGINEERING
04 MONTHS COMPREHENSIVE STUDY
ONLINE
Original 50,000 PKR
AI Foundations Key Knowledge Areas
• AI Basics
• History of AI
• Rule Based AI to GenAI to Agentic
• AI Enterprise AI use cases
• Modern AI, Current Landscape,
• Job Opportunities
• Role of Mathematics,
• Statistics, Algorithms, Programming,
• Today’s Programming, Assisted Programming
• Programming Concepts / Building Blocks Introduction
Programming Foundations Programming with Python
• Python Intro
• IDEs
• Installations
• Variables
• Conditional Statements
• Loops
• Casting
• Strings
• Booleans
• Lists, Tuples, Sets, Dictionaries
• User defined functions
• Built in Functions
• Range, Regex,
• Libraries Installations PIP
• OOP Concepts
• Classes
• Constructor
• User Defined functions
• Polymorphism
• Inheritance
• Encapsulation
• Importing Modules, libraries
• Utilizing modules
Python for AI and DS
• Python for AI
• Essential Python / mathematics
• Numpy Library
Numpy Important Functions
• Pandas Library
Pandas Important Functions
• Practical Examples
Data Workflows
• Typical Data Workflows / Pipeline
• EDAs
• Data cleaning
• Data Wrangling
• Feature Engineering
• Practical Examples
Machine Learning (Supervised ML)
Regression
Linear Regression
MSE
MAE
R²
Classification,
Logistic Regression
Support Vector Machines
Confusion Matrix
TP-FP-TN-FN
Precision
Recall
F1-Score
Specificity
TPR
FPR
Practical Examples
Statistical Features
Class Balance Techniques
Random Sampling
Over Sampling
SMOTE
ADASYN
Under Sampling
TOMEK Links
Near Miss
Machine Learning (Unsupervised ML)
• Clustering
K-Means
DBSCAN
• Dimensionality Reduction
Principal Component Analysis
Covariance, PC1, PC2
• Practical Examples
Reinforcement Learning
• RL Algorithm
• Q-Learning
• On Policy / Off Policy
• SARSA
• Practical Example
Advance ML
- Additional ML Algos
- Ensemble Learning
- Bagging
- Random Forest
- Boosting
- XgBoost / AdaBoost
- Practical Examples
SQL Foundations For Machine Learning
- DDL
- DML
- DCL
- TCL
- Queries
- Selection
- Updating
- Deletion
- Clauses
- Joins
- Constraints
- Aggregations
Deep Learning
• Neural Network Basics
• Perceptron History
• Multi-Layer Perceptrons (MLPs)
• Activation Functions
• Sigmoid
• ReLu
• Softmax
• Forward & Backpropagation
• Loss Functions
• Binary Cross entropy
• Categorical Cross entropy
• Sparse categorical cross entropy
• Binary Data
• Little Endian / Big Endian
• Simple Model Evaluation
• Accuracy & Confusion Matrix
• Training Accuracy
• Training Loss
• Validation Accuracy
• Validation Loss
• Practical Implementation ANN
xamples
NLP
- Text Preprocessing:
- Tokenization,
- Stop words
- Stemming
- Lemmatization
- Bag of Words
- TF-IDF
- Word Embedding (Word2Vec)
- Sentiment Analysis
- Tools: NLTK, spaCy
Linguistic Analysis
LLMs
- LLMs Introduction
- LLM-Specific Tokenization & Embeddings
- Pre-training vs Fine-tuning (concepts)
Computer Vision
- Convolutions (Intuition)
- Convolutional Neural Networks (CNNs)
- Stride
- Kernels
- Common Kernels
- Simple Image Classification
- Image Segmentation (overview)
- Object Detection
- Practical Examples
RAG
- RAG Concepts
- Problems with LLMs
- Practical Example
- Prompt Controlling
Transformers
- Introduction to Sequence Models
- Attention Mechanism (intuitive explanation)
- Encoder–Decoder Architecture (conceptual)
- Pretrained Models Overview: GPT, BERT
Generative AI
• What is Generative AI?
• Applications in Text, Images, Audio
• Human-AI Collaboration Examples
• Responsible AI Overview
Groq API
• Practical Examples
Prompt Engineering
• Basic Prompt Patterns
• Common Prompt Types
• Chain-of-Thought Prompts
• Crux by Toseef, Context-of-Context
Applied AI
• Groq based Chatbots
• Pretrained models
• Computer Vision Applications
• DeepSeek based Apps
• Qwen based Apps
• ChatGPT based Apps
• Domain-Specific Examples
MASTER PYTHON, DATA WORKFLOWS, NLP, COMPUTER VISION & GENERATIVE AI
Our Four-Month Comprehensive AI & Machine Learning Course is an intensive, industry-aligned learning program designed for serious learners who want to move beyond fundamentals and master advanced, real-world AI systems.
This program includes everything covered in our 2-month AI/ML course, plus Natural Language Processing (NLP), Computer Vision, Transformers, and API-driven AI development using OpenAI, DeepSeek, and Groq.
This is a challenging, vibrant, and career-focused learning experience built to prepare you for modern AI roles.
TNBits delivers professionally designed training and capacity-building programs focused on Artificial Intelligence and advanced IT technologies. Our courses are co-created by experienced academicians and industry practitioners, ensuring a strong balance between theoretical foundations and real-world application.
Expert Tutors
Courses follow a disciplined structure grounded in established principles
Content is shaped to reflect how concepts are applied in real-world environments
Learning progresses logically, supporting both understanding and application
Practicals Oriented
Course material is framed around practical scenarios and real operational contexts
Emphasis on applying concepts to realistic problems and use cases
Encourages sound judgment, analytical thinking, and professional discipline
Beginner's Friendly
Programs are suitable for beginners, early-career professionals, and experienced learners
Foundational pathways do not assume prior specialization
Designed to accommodate learners from diverse academic and professional backgrounds
Monthly Installments
Monthly installment options available
Fee structure designed to support sustained learning and long-term development
- Special Discount offers on Lump Sum payments and early bird registrations
WHY THIS COURSE STANDS OUT
16 weeks of intensive, structured learning
Covers classical ML + modern Generative AI
Hands-on projects using real APIs and real data
Career-focused curriculum aligned with industry demand
Designed for learners aiming for AI Engineer, ML Engineer, or Data Scientist roles
FOUR-MONTH COMPREHENSIVE AI & MACHINE LEARNING COURSE
BEGINNER TO ADVANCED — NO PRIOR EXPERIENCE REQUIRED
Our Four-Month AI & Machine Learning Course is a complete beginner-to-advanced learning program designed for students from all backgrounds.
The first two months cover the full beginner-level AI/ML curriculum, making this course suitable even if you have no prior experience in programming, data science, or AI.
The remaining two months take you into advanced AI, Machine Learning, and Generative AI, ensuring a smooth and structured learning progression.
WHO CAN ENROLL
This course is ideal for:
Beginners with zero technical background
Students from any academic discipline
Professionals looking to switch careers into AI
Developers wanting to advance into modern AI and ML
Anyone interested in Artificial Intelligence and Machine Learning
No prior coding or AI knowledge is required.
WHY THIS COURSE IS DIFFERENT
COMPLETE AI ECOSYSTEM COVERAGE
Covers the full spectrum of Artificial Intelligence — from Python and Machine Learning to NLP, Computer Vision, Transformers, and Generative AI.BALANCE OF THEORY AND REAL-WORLD PRACTICE
Concepts are taught with strong theoretical foundations and immediately applied through hands-on implementation and real datasets.MODERN, INDUSTRY-RELEVANT CURRICULUM
Includes cutting-edge technologies actively used in the industry such as OpenAI API, DeepSeek API, and Groq-powered AI systems.END-TO-END AI SYSTEM DEVELOPMENT
Learn how to design, train, evaluate, and deploy complete AI workflows, not just isolated models.FOCUS ON REAL APPLICATIONS, NOT JUST TOOLS
Emphasis on solving real-world problems using AI rather than memorizing algorithms or libraries.PROJECT-DRIVEN LEARNING APPROACH
Every major concept is reinforced through practical projects, helping build a strong, job-ready portfolio.CLASSICAL ML + ADVANCED AI TOGETHER
Combines traditional Machine Learning techniques with modern Deep Learning and Generative AI, ensuring long-term relevance.API-BASED AI DEVELOPMENT SKILLS
Gain experience building AI-powered applications using production-level APIs used by real companies.CAREER-FOCUSED SKILL DEVELOPMENT
Designed to develop problem-solving, model optimization, and system-thinking skills required for AI Engineer and ML roles.INTENSIVE, HIGH-IMPACT LEARNING EXPERIENCE
A challenging and vibrant program built to push learners beyond surface-level understanding.
Enroll Today
Take the first step towards becoming an AI and Machine Learning expert. This is your chance to gain hands-on experience, advanced knowledge, and a portfolio that stands out.