Build Real-World AI Applications with Python: Learn, Code & Deploy Like a Pro!

Build Real-World AI Applications with Python: Learn, Code & Deploy Like a Pro!

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is like giving superpowers to machines. It enables computers to do things that usually require human intelligence—like learning from experience, solving problems, understanding natural language, recognizing patterns in images or sounds, and making decisions.

Imagine your phone not just responding to commands, but actually understanding you, adapting to your needs, and even predicting what you’ll want next. That’s AI in action. It’s the brain behind self-driving cars, intelligent assistants, facial recognition, personalized recommendations, and even machines that create art or music.

In simple terms, AI gives machines the ability to “think” and “learn”—bringing science fiction into reality.

Why Learn Artificial Intelligence?

Learning AI is like unlocking the future. With AI, you’re not just coding—you’re building machines that learn, reason, and evolve.

Whether it’s:

• Designing chatbots that talk like humans,
• Building systems that detect diseases from images,
• Or creating recommendation engines like Netflix and Amazon…

AI is the key to innovation across industries—healthcare, finance, education, entertainment, and more. And in the job market? AI skills are in massive demand. Organizations worldwide are looking for professionals who can bring intelligence to their systems. By mastering AI, you’re equipping yourself with one of the most sought-after and future-proof skill sets in tech. You won’t just be learning—you’ll be shaping the future.

What This Course Offers You

Join our immersive, project-based course designed to turn you into a confident AI developer using Python.

• Learn the foundations of AI from scratch
• Build real-world projects from day one
• Get hands-on with powerful tools and libraries (like NumPy, Pandas, Scikit-learn, TensorFlow)
• Explore AI case studies used in the real world
• Deploy your own AI apps and models
• Get career-ready with portfolio-worthy projects

What Makes This Course Different?

• Real Projects, Real Skills: Go beyond theory—create AI models you can actually deploy.
• Python-Powered: Python is the #1 language for AI—easy to learn, powerful to build with.
• Industry-Relevant: Stay ahead of the curve with the tools and techniques used by professionals.
• Creative Thinking Meets Smart Coding: AI isn’t just about code; it’s about ideas. Learn to innovate.

Your Journey Starts Here

Whether you’re a student, tech enthusiast, developer, or future data scientist—this course is your gateway to the fascinating world of Artificial Intelligence.

Join a community of future-ready creators, innovators, and AI changemakers.

Learn. Code. Innovate. Deploy.

Build the future—one intelligent application at a time.

Module 1: Supervised and Unsupervised Learning with Python – Part 01

Objective: Introduce the fundamentals of AI, data handling, and basic supervised learning methods using Python.

Topics:

• AI overview and real-world applications
• Turing Test, intelligent agents
• Supervised vs. unsupervised learning
• Data preprocessing and label encoding
• Classification with logistic regression, Naïve Bayes, SVM
• Confusion matrix analysis
• Practical: Classifying income data

Outcomes: Learners will understand core AI concepts and implement basic classifiers using real datasets in Python.

Module 2: Supervised and Unsupervised Learning with Python – Part 02

Objective: Expand skills in regression, decision trees, ensemble learning, clustering, and recommendation systems.

Topics:

• Regression (single/multiple) for predictions
• Ensemble methods: Decision Trees, Random Forests
• Class imbalance handling and parameter tuning
• K-means clustering, model quality evaluation
• KNN classifiers and recommendation systems
• Practical: Market segmentation, movie recommendations

Outcomes: Participants will be able to build predictive and unsupervised models for business intelligence and personalization tasks.

Module 3: AI with Python – Sequence Learning & NLP (Part 01)

Objective: Introduce text processing, natural language understanding, and basic NLP-based AI applications.

Topics:

• NLP package setup
• Tokenization and lemmatization
• Bag-of-Words model
• Text classification and gender prediction
• Sentiment analysis
• Topic modeling with LDA

Outcomes: Learners will gain hands-on experience in building AI models for text data, sentiment analysis, and topic extraction.

Module 4: Sequence Learning with Python – Part 02

Objective: Dive deeper into handling sequential and time-series data, audio processing, and real-world applications like stock prediction and speech recognition.

Topics:

• Time-series data manipulation with Pandas
• Statistical feature extraction from sequences
• Hidden Markov Models & Conditional Random Fields
• Stock market trend analysis
• Audio signal processing and transformation
• Speech feature extraction and recognition
• Synthesizing music using Python

Outcomes: Learners will be able to analyze, process, and interpret complex sequential data like stock prices and speech signals for intelligent system development.

Module 5: Heuristic Search with Python – Part 01

Objective: Introduce logic programming and symbolic reasoning using Python to solve structured AI problems.

Topics:

• Introduction to logic-based AI
• Python package setup for logic programming
• Expression matching and prime validation
• Family tree and geographical data parsing
• Building solvers for logical puzzles

Outcomes: Participants will understand logic-based problem-solving and apply rule-based approaches to structured knowledge domains.

Module 6: Heuristic Search with Python – Part 02

Objective: Master heuristic and evolutionary search techniques, and apply them in AI problem-solving and game bots development.

Topics:

• Constraint satisfaction and local search
• Simulated annealing and greedy algorithms
• 8-puzzle, maze solving, and region-coloring
• Genetic algorithms for optimization
• Building intelligent agents and game bots
• Minimax, Alpha-Beta Pruning, Negamax
• AI bot development for Tic-Tac-Toe, Connect Four, Hexapawn

Outcomes: Learners will design intelligent AI agents using search algorithms and build game-playing bots that learn, adapt, and compete effectively.

Module 7: Deep Neural Networks with Python – Part 01

Objective: Learn the foundations of computer vision and object tracking using OpenCV and classic visual AI techniques.

Topics:

• OpenCV setup and image processing
• Frame differencing and color-based tracking
• Background subtraction and CAMShift
• Optical flow-based motion tracking
• Face detection and real-time tracking

Outcomes: Learners will be able to build basic computer vision applications for detecting, tracking, and analyzing objects in videos and images.

Module 8: Deep Neural Networks with Python – Part 02

Objective: Master the fundamentals of neural networks, recurrent models, convolutional models, and reinforcement learning through hands-on projects.

Topics:

• Artificial neural networks (ANNs) and perceptrons
• Multilayer and recurrent neural networks (RNNs)
• Optical Character Recognition (OCR)
• Reinforcement learning: agent-environment setup
• Convolutional Neural Networks (CNNs)
• Image classification using ANN and CNN

Outcomes: Participants will gain practical skills in deep learning by building OCR systems, reinforcement learning agents, and image classifiers using neural network models.

Module 9: Develop Your Live AI Project – Part 01

Objective: Apply AI models and evaluation techniques to real-world datasets for text classification, sentiment analysis, and decision-making systems.

Topics:

• Evaluation metrics and classification strategy
• Decision Trees and Random Forests
• Predictive models for student performance and bird species
• YouTube spam detection using Bag of Words
• Sentiment analysis with Word2Vec

Outcomes: Learners will be able to build and evaluate intelligent classifiers for various domains, including education, text analysis, and spam detection.

Module 10: Develop Your Live AI Project – Part 02

Objective: Capstone your AI journey by developing and improving deep learning models for music classification, spam filtering, and image-based recognition.

Topics:

• Audio classification using neural networks
• Neural spam filtering
• CNNs for handwritten symbol recognition
• Migrating classical models to deep learning
• Image-based bird species identification

Outcomes: Participants will complete deployable AI projects, demonstrating their ability to combine theory and practice in building deep learning solutions for real-world problems.

Become Job-Market Ready with Practical AI Skills

Step into the world of real, applied Artificial Intelligence. This hands-on course goes beyond theory to empower you with the tools, techniques, and mindset to build AI solutions that matter.

Whether you’re a data enthusiast, software developer, researcher, freelancer, or aspiring AI expert—this course is designed to help you:

Design and develop real-world AI applications

• Build powerful models using Python and modern AI libraries
• Tackle real-life challenges in NLP, computer vision, time series, and speech recognition
• Deploy AI models and applications with confidence and clarity

Don’t just study AI—apply it. Don’t just build—innovate!

Why Join This Course?

• Learn cutting-edge AI concepts through real-world projects
• 100% hands-on from Day One
• Covers Deep Learning, NLP, Time-Series, Audio Analysis, OCR, and more
• Learn industry-ready problem-solving approaches
• Earn a Certificate of Completion to showcase your skills
• Hybrid mode: Live Online Classes + In-Person Sessions

Tools & Technologies You’ll Master

• Python, NumPy, Pandas, Matplotlib
• Scikit-learn, TensorFlow, Keras, OpenCV
• LibROSA for audio signal processing
• NLTK, spaCy for natural language processing
• Jupyter Notebook, Google Colab
• Model deployment tools and techniques

Enrollment & Payment Information

Certificates will be awarded to all participants upon successful completion.

Seats are limited—Enroll now! Secure your seat by transferring the course fee to:

Bank Details:

• Account Name: TalhaTraining
• Account No.: 2141116000973
• Bank Name: Prime Bank Limited
• SWIFT Code: PRBLBDDH
• Routing Number: 170263614

📩 After making the payment, please email us:

• Full Name
• Mobile Number
• Payment Slip

📧 Email to:

• training@talhatraining.com
• talhatraining@gmail.com

💬 Need Assistance? Get in Touch!

We’re happy to help you decide if this course is right for your goals.

📱 Call / WhatsApp: +8801712742217

📧 Email: training@talhatraining.com | talhatraining@gmail.com

🌐 Website: talhatraining.com | hostbari.com

Start Building AI That Matters

Join a vibrant learning community of AI innovators, problem-solvers, and professionals. Whether you’re developing solutions for healthcare, finance, education, or tech startups, this course gives you the skills to lead and succeed.

👉 Learn. Code. Deploy.

Be the AI professional every future-ready team needs!