ARTIFICIAL INTELLIGENCE ⭕
Artificial Intelligence
Batch starts Every 5th, 15th, 25th of Every Month
- 2487 students
- Duration 2-3 Months
Descriptions
This course is designed to equip learners with foundational and practical knowledge of Artificial Intelligence. Beginning with the essentials of Python programming, the program gradually introduces data handling, machine learning concepts, neural networks, natural language processing, and project-based applications of AI. With a blend of theoretical understanding and hands-on experience, students will build multiple small projects throughout the course and end with a capstone project that simulates real-world AI challenges.
By the end of the course, learners will be confident in:
Writing Python code for AI tasks
Implementing ML algorithms
Handling data preprocessing
Working with neural networks
Building mini and full-scale AI solutions
Key Points
- Python Programming for Data Analysis
- Statistics & Data Visualization
- Machine Learning & Supervised Learning
- Unsupervised Learning & Clustering
- Natural Language Processing (NLP) & Deep Learning
- Model Deployment & Big Data with Cloud
Course Lessons
- Topics: History of AI, AI vs ML vs DL, Real-world applications
- Capstone: Present 3 real-world AI use cases with tech stacks
- Homework: Write a 1-page summary on how AI is impacting daily life
- Topics: Python basics, data types, control structures, functions, libraries (NumPy, Pandas)
- Capstone: Build a mini calculator or data summarizer using Python
- Homework: Practice 10 basic programs and submit notebook
- Topics: Data cleaning, missing values, encoding, normalization, data splitting
- Capstone: Clean and prepare a raw dataset for ML modeling
- Homework: Submit a cleaned dataset with documentation
- Topics: Supervised vs Unsupervised, regression, classification
- Capstone: Train a classification model (e.g., Decision Tree) on sample data
- Homework: Train and evaluate a linear regression model on custom data
Topics: Neural Networks, activation functions, loss functions, training basics
Capstone: Build a simple ANN using TensorFlow or Keras
Homework: Explain the working of a neural network layer-by-layer
Topics: Image data, CNNs, OpenCV basics
Capstone: Create an image classifier for 2-3 object categories
Homework: Explore and summarize 3 real-world CV applications
Topics: Text cleaning, vectorization (TF-IDF), sentiment analysis basics
Capstone: Build a sentiment analyzer using a movie reviews dataset
Homework: Extract and clean data from text using Python
Topics: Confusion matrix, accuracy, precision, recall, hyperparameter tuning
Capstone: Compare 3 models using metrics and suggest the best
Homework: Create a model evaluation report on any open dataset
Projects
Project Goal: Build a full pipeline AI project addressing a real-world issue — e.g., predicting disease, detecting fake news, or analyzing social media sentiment.
Deliverables:
Problem statement
Data source and preprocessing steps
Model architecture
Evaluation metrics
Final report + demo presentation
Instructor
Masters in AI & ML
This course includes:
- 35+ hours on-demand video
- Lifetime LMS Access
- Course Completion Certificate
- Co-Branded Internship Completion Certificate
- 2 Minor Projects and 1 Major Project
Upon successfully completing this course, you will receive a certificate of completion that helps potential employers assess your proficiency.
Government Certified
Earn NSDC Certification
Benefits of NSDC Certification:
- Government-Recognized Credential
- Industry-Accepted Validation
- Enhanced Employability
- Alignment with Skill India Mission
- Added Value for Higher Education & International Opportunities
- National Skill Registry Entry
Hear it From Them
Ambitious People ❤️ SmartED ✨
