AI & Machine Learning Professional Program
AI & Machine Learning Professional Program
AI & Machine Learning Professional Program
Build industry-ready skills with practical training, expert guidance and career-focused learning.
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180 Hours
Monday – Friday
Offline / Online
16 Modules
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📞 +91 8086 651 651Course Overview
Through hands-on projects and industry-focused training, learners gain the expertise needed to develop predictive models and AI-powered solutions for real-world applications.
Through hands-on labs and industry-oriented projects, students learn how applications are developed, deployed, monitored, scaled, and maintained in modern cloud environments.
By the end of the programme, students will:
- Build machine learning models
- Perform predictive analytics
- Apply deep learning concepts
- Deploy AI solutions
COURSE MODULES
01 | Introduction to Artificial Intelligence & Python Programming
Artificial Intelligence is transforming every industry, from healthcare and finance to retail and manufacturing. This module introduces students to the fundamentals of AI, Machine Learning, and Data Science while building a solid foundation in Python programming—the world's most popular language for AI development.
What You'll Learn
- Introduction to Artificial Intelligence, Machine Learning and Data Science
- Applications of AI across industries
- Python installation and development environment
- Variables, Data Types and Operators
- Conditional Statements and Loops
- Functions and Modules
- Object-Oriented Programming (OOP)
- File Handling
- Exception Handling
- Working with Python Libraries
02| Data Science Fundamentals
Data is the foundation of Artificial Intelligence. Students will learn how to collect, clean, organize, and prepare datasets for machine learning models using industry-standard Python libraries.
What You'll Learn
- Introduction to Data Science
- NumPy Arrays
- Pandas DataFrames
- Reading CSV and Excel files
- Data Cleaning Techniques
- Handling Missing Values
- Data Transformation
- Feature Engineering Basics
- Data Aggregation
- Exploratory Data Analysis
03| Statistics for Machine Learning
Machine Learning algorithms rely heavily on statistics. This module provides students with the mathematical concepts necessary to understand how predictive models work.
What You'll Learn
- Descriptive Statistics
- Mean, Median and Mode
- Standard Deviation
- Probability
- Probability Distributions
- Correlation
- Covariance
- Hypothesis Testing
- Sampling Techniques
- Statistical Significance
04| Data Visualization
Learn how to transform raw data into meaningful visual insights that support better business decisions.
What You'll Learn
- Introduction to Data Visualization
- Matplotlib
- Seaborn
- Line Charts
- Bar Charts
- Scatter Plots
- Histograms
- Heatmaps
- Distribution Plots
- Business Dashboard Basics
05| Beginner Project
Students will apply everything learned by completing practical projects.
Projects
- Student Performance Analysis
- Sales Dashboard
- COVID Data Analysis
- Employee Dataset Analysis
06 | Machine Learning Fundamentals
This module introduces students to the core concepts of Machine Learning and teaches how computers learn from data to make predictions without explicit programming.
What You'll Learn
- Types of Machine Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Training and Testing Data
- Feature Selection
- Model Evaluation
- Bias and Variance
- Overfitting and Underfitting
- Cross Validation
07| Machine Learning Algorithms
Students will develop predictive models using the most widely used machine learning algorithms in the industry.
What You'll Learn
- Linear Regression
- Multiple Regression
- Logistic Regression
- Decision Trees
- Random Forest
- K-Nearest Neighbors
- Support Vector Machine
- Naive Bayes
- K-Means Clustering
- Model Accuracy Comparison
08| Feature Engineering
High-quality features significantly improve machine learning performance. This module focuses on transforming raw data into useful model inputs.
What You'll Learn
- Feature Selection
- Feature Scaling
- Normalization
- Standardization
- Encoding Categorical Variables
- Dimensionality Reduction
- Principal Component Analysis (PCA)
- Feature Extraction
09| AI Tools & Automation
Explore how modern AI tools accelerate development and improve productivity.
What You'll Learn
- ChatGPT for Python Development
- GitHub Copilot
- AI Code Generation
- Prompt Engineering
- AI Productivity Tools
- AI Documentation
- Workflow Automation
- AI-assisted Debugging
10| Intermediate Projects
Students will apply everything learned by completing practical projects.
Projects
- Student Performance Analysis
- Sales Dashboard
- COVID Data Analysis
- Employee Dataset Analysis
11 | Deep Learning
Deep Learning enables computers to recognize images, speech, and complex patterns using artificial neural networks.
What You'll Learn
- Introduction to Deep Learning
- Artificial Neural Networks
- Activation Functions
- Forward & Back Propagation
- TensorFlow
- Keras
- Model Training
- Model Optimization
- Hyperparameter Tuning
- Model Evaluation
12| Computer Vision
Students will build intelligent applications capable of understanding and analysing images.
What You'll Learn
- Image Processing Basics
- OpenCV
- Image Classification
- Object Detection
- Face Detection
- Face Recognition
- Image Segmentation
- OCR Basics
- CNN Introduction
13| Natural Language Processing (NLP)
Learn how AI understands and processes human language to build intelligent chatbots and text analysis systems.
What You'll Learn
- Text Preprocessing
- Tokenization
- Stop Words Removal
- Stemming
- Lemmatization
- Sentiment Analysis
- Text Classification
- Named Entity Recognition
- Large Language Model Basics
- AI Chatbot Fundamentals
14| Model Deployment
Learn how to deploy machine learning models as real-world applications.
What You'll Learn
- Flask Framework
- REST APIs
- API Integration
- Model Serialization
- Deployment using Streamlit
- Cloud Deployment Basics
- Docker Introduction
- Model Versioning
- Application Testing
15| AI Engineering & MLOps
Modern AI projects require continuous monitoring and automation. Students will learn the fundamentals of production-ready AI systems.
What You'll Learn
- Introduction to MLOps
- Machine Learning Lifecycle
- CI/CD for ML
- Model Monitoring
- Model Retraining
- Experiment Tracking
- Data Version Control
- AI Infrastructure Basics
16| Generative AI & Large Language Models
Understand the technologies driving today's AI revolution and learn how to build applications powered by advanced language models.
What You'll Learn
- Introduction to Generative AI
- Large Language Models (LLMs)
- Prompt Engineering Techniques
- AI Content Generation
- AI Coding Assistants
- Retrieval-Augmented Generation (RAG) Concepts
- AI Ethics and Responsible AI
- Building AI-powered Applications
- AI Agents and Workflow Automation
Software & AI Tools Covered
Throughout the Professional Program, students will gain practical experience with:
- OpenCV
- Flask
- Streamlit
- Git & GitHub
- Docker (Introduction)
- VS Code
- ChatGPT
- GitHub Copilot
- Hugging Face
- Google Gemini
- Ollama (Introduction to Local LLMs)
Career Opportunities
After completing the Professional Program, learners can pursue roles such as:
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- Data Analyst
- Deep Learning Engineer
- NLP Engineer
- Computer Vision Engineer
- AI Application Developer
- MLOps Engineer (Entry Level)
- Business Intelligence Analyst
- Python Developer (AI Focus)
- Generative AI Developer
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Placements
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Software Developer
Destimona thomas
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Course Cetificate
Certificate
The Cloud Computing & DevOps Professional Program at Jigsaw TechnoHub is designed to help learners build practical skills in cloud infrastructure, Linux, networking, virtualization, DevOps practices, automation, containerization, and cloud deployment.
- Work with Linux and cloud infrastructure
- Understand networking and virtualization
- Deploy applications on cloud platforms
- Use Git and GitHub for version control
- Build and manage Docker containers
- Create CI/CD pipelines
- Automate infrastructure deployment
- Work with Infrastructure as Code
Ready to Build Your Future?
Your journey from graduate to professional starts here.Join Jigsaw TechnoHub and gain the skills, confidence, and industry exposure needed to succeed in today's competitive job market.