Practical AI Development Program

  • High Demand In The It Industry: Ai is in demand because companies use it for automation, smart applications, customer support, data analysis, and decision-making.
  • Useful In Multiple Career Fields: Ai is used in healthcare, finance, education, e-commerce, cybersecurity, marketing, automation, and software development.
  • Build Smart Real-world Applications: Learners can create chatbots, recommendation systems, prediction tools, ai assistants, automation workflows, and intelligent business solutions.
1.5 Months ₹11,999 ₹8,999
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Course Overview

Artificial Intelligence is a modern technology that enables machines to think, learn, analyze data, understand language, recognize images, and make intelligent decisions. This 45 days course helps learners build a strong foundation in AI concepts, Python for AI, machine learning basics, data handling, NLP basics, computer vision basics, generative AI, prompt engineering, and practical AI project development.

Course with Live Project

No Refund Available

Ai Concepts And Intelligent Systems: Learners Understand Ai Fundamentals, Intelligent Decision-making, Automation, Ai Workflow, And Real-world Ai Applications.

Machine Learning, Nlp, And Computer Vision Basics: Work With Basic Prediction Systems, Chatbot Logic, Text Processing, Image Recognition Concepts, And Beginner-level Ai Models.

Practical Ai Project Development: Develop Projects Like Ai Chatbots, Career Recommendation Assistants, Smart Study Planners, Resume Screening Tools, And Simple Ai Automation Systems.

Course Content

  • • Understanding artificial intelligence concepts
  • • Exploring history and evolution of ai
  • • Learning different types of ai
  • • Understanding real-world ai applications
  • • Exploring ai across multiple industries
  • • Comparing ai, ml, and deep learning
  • • Understanding ai workflow process

  • • Learning python programming fundamentals
  • • Understanding variables and data types
  • • Working with conditional statements logic
  • • Using loops for program execution
  • • Creating functions and reusable modules
  • • Managing data with python collections
  • • Exploring python libraries for ai

  • • Understanding data types in ai
  • • Learning statistics for artificial intelligence
  • • Understanding mean, median, and mode
  • • Exploring probability and predictions
  • • Understanding correlation between variables
  • • Learning matrix and vector concepts
  • • Exploring linear algebra for ai

  • • Understanding numpy for data processing
  • • Learning pandas for data analysis
  • • Managing data using dataframes
  • • Reading csv and excel files
  • • Cleaning and preparing datasets
  • • Handling missing data efficiently
  • • Transforming data for ai models

  • • Understanding machine learning concepts
  • • Exploring types of machine learning
  • • Learning supervised learning techniques
  • • Understanding unsupervised learning concepts
  • • Working with regression models
  • • Exploring classification algorithm basics
  • • Measuring prediction and accuracy

  • • Understanding deep learning fundamentals
  • • Learning artificial neural networks
  • • Exploring perceptron working concepts
  • • Understanding activation function basics
  • • Learning hidden layer concepts
  • • Exploring real-world deep learning uses

  • • Understanding natural language processing
  • • Learning basic text processing techniques
  • • Understanding text tokenization process
  • • Removing stop words from text
  • • Exploring chatbots and language models
  • • Understanding sentiment analysis concepts
  • • Working with language-based ai

  • • Understanding computer vision concepts
  • • Learning basic image processing methods
  • • Understanding face detection techniques
  • • Exploring object detection concepts
  • • Learning opencv library basics
  • • Understanding ai in healthcare imaging

  • • Understanding generative artificial intelligence
  • • Learning large language model basics
  • • Exploring chatgpt and ai assistants
  • • Understanding prompt engineering concepts
  • • Using ai for content generation
  • • Exploring ai automation techniques
  • • Learning responsible ai practices

  • • Planning real-world ai applications
  • • Preparing datasets for ai models
  • • Training beginner-level ai models
  • • Testing model performance accuracy
  • • Creating ai-based mini projects
  • • Understanding ai deployment basics
  • • Presenting ai project outcomes

  • • Ai ethics & bias analysis
  • • Nlp text processing exercise
  • • Chatbot conversation logic design

Skills Developed with Artificial Intelligence Course

Ai Fundamentals: Understand ai concepts, types of ai, ai workflow, real-world applications, and the difference between ai, ml, and deep learning.
Python For Ai: Learn python basics, functions, modules, data structures, file handling, oop basics, and logic building for ai applications.
Data Handling Basics: Work with numpy, pandas, data cleaning, missing values, basic transformations, and exploratory data understanding.
Machine Learning Basics: Learn supervised learning, unsupervised learning, regression, classification, clustering, model training, and prediction concepts.
Nlp Basics: Understand text processing, tokenization, stop words, chatbot logic, sentiment analysis basics, and language-based ai systems.
Computer Vision Basics: Learn image processing concepts, face detection basics, object detection overview, opencv basics, and image recognition use cases.
Generative Ai Concepts: Understand chatgpt, ai assistants, text generation, content generation, ai tools, and responsible ai usage.
Prompt Engineering: Practice writing effective prompts for content creation, learning support, coding help, automation tasks, and ai productivity.
Ai Tools Usage: Work with python, jupyter notebook, google colab, scikit-learn basics, opencv basics, and modern ai productivity tools.
Ai Project Development Skills: Practice planning, building, testing, documenting, and presenting beginner-to-intermediate ai projects.

Career Opportunities after Artificial Intelligence Course

This course opens doors to multiple high-demand career paths across industries.

Ai Intern:

Support basic ai projects through data preparation, prompt writing, chatbot testing, and beginner-level ai implementation.

Ai Project Assistant:

Help teams with ai research, dataset understanding, model testing, documentation, and project coordination.

Prompt Engineering Assistant:

Create and improve prompts for chatbots, content generation, automation workflows, and ai productivity tools.

Junior Ai Developer:

Build basic ai applications such as chatbots, recommendation tools, ai planners, and automation-based systems.

Ai Automation Assistant:

Work on simple automation tasks using ai tools, prompt workflows, and beginner-level intelligent systems.

Why Enroll in Artificial Intelligence with Solitaire Learning?

Beginner-friendly Ai Training: The course starts from ai fundamentals and gradually moves toward python, ml basics, nlp, computer vision, and generative ai.
Practical Project-based Learning: Learners work on real-world ai projects like chatbots, recommendation assistants, study planners, and ai automation tools.
Industry-relevant Ai Tools: The course covers python, google colab, scikit-learn basics, opencv basics, chatgpt, prompt engineering, and ai productivity tools.
Mentor-guided Learning: Learners receive mentor support for concept clarity, project development, prompt practice, doubt solving, and portfolio preparation.
Strong Foundation For Advanced Ai Courses: The course builds a solid base before moving into 2 months, 3 months, 4 months, or 6 months artificial intelligence programs.

Ready to Take the Next Step in Your Career?

Join our expert-led training program, gain industry-recognized skills, and move closer to your professional goals. Seats are limited — enroll today!

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