Duration :- 8 Months
Artificial Intelligence Course – Master the Future of Technology
Explore the cutting-edge world of Artificial Intelligence (AI) with Code Codence’s comprehensive AI course! Designed for aspiring AI professionals, this course covers essential AI concepts, tools, and techniques to help you develop intelligent systems capable of learning, reasoning, and decision-making. From machine learning to neural networks, this course offers a hands-on approach to mastering AI through real-world applications and projects.
What You’ll Learn:
- Introduction to AI:
- Understand the fundamentals of AI, its history, and real-world applications.
- Machine Learning (ML):
- Supervised, unsupervised, and reinforcement learning techniques.
- Build predictive models using algorithms like linear regression, decision trees, and SVM.
- Neural Networks & Deep Learning:
- Explore neural networks, CNNs, RNNs, and advanced architectures like GANs and transformers.
- Natural Language Processing (NLP):
- Work on text data to develop chatbots, sentiment analysis, and language translation models.
- Computer Vision:
- Learn image processing, object detection, and facial recognition using deep learning frameworks.
- AI Tools and Frameworks:
- Master popular AI tools like Python, TensorFlow, PyTorch, Keras, and Scikit-Learn.
- Ethics and AI Governance:
- Understand ethical considerations and biases in AI and their societal implications.
- Capstone Projects:
- Apply your skills to real-world projects like autonomous systems, recommendation engines, or AI-powered apps.
Course Highlights:
- Duration: Flexible (customizable based on learning pace)
- Format: Online or Hybrid (interactive sessions and recorded lectures)
- Tools Covered: Python, TensorFlow, PyTorch, Keras, Scikit-Learn, OpenCV
- Hands-on Projects: Industry-focused projects to build a robust portfolio
- Mentor Support: Expert guidance through one-on-one mentorship
- Certification: Receive a professional AI certification upon course completion
Join Code Codence’s AI course to unlock endless possibilities in AI innovation and become a leader in the world of artificial intelligence!
For more details about the Artificial Intelligence Using Python course, contact us here or chat with us directly on WhatsApp — we’re here to help you get started!
Curriculum
- 8 Sections
- 63 Lessons
- 32 Weeks
- PYTHON (3 Months)35
- 1.1Module 1: Introduction to Python
- 1.2Module 1 Introduction to Python (Assignment Questions)1 Week
- 1.3Module 2: Writing and Executing Your First Python Program
- 1.4Module 2 Writing and Executing Your First Python Program (Assignment Questions)1 Week
- 1.5Module 3: Python Language Fundamentals
- 1.6Module 3 Python Language Fundamentals(Assignment Questions)1 Week
- 1.7Module 4: Standard Data Types
- 1.8Module 4 Standard Data Types (Assignment Questions)1 Week
- 1.9Module 5: Python Conditional Statements
- 1.10Module 5 Python Conditional Statements (Assignment Questions)1 Week
- 1.11Module 6: Looping Statements
- 1.12Module 6 Looping Statements (Assignment Questions)1 Week
- 1.13Module 7: String Handling
- 1.14Module 7 String Handling (Assignment Questions)1 Week
- 1.15Module 8: Python List
- 1.16Module 8 Python List (Assignment Questions)1 Week
- 1.17Module 9: Python Tuple
- 1.18Module 9 Python Tuple (Assignment Questions)1 Week
- 1.19Module 10: Python Set
- 1.20Module 10 Python Set & Frozenset (Assignment Questions)1 Week
- 1.21Module 11: Python Dictionary
- 1.22Module 11 Python Dictionary (Assignment Questions)1 Day
- 1.23Module 12: Python Functions
- 1.24Module 12 Python Functions (Assignment Questions)1 Week
- 1.25Module 13: Modules & Packages
- 1.26Module 13 Modules & Packages (Assignment Questions)1 Week
- 1.27Module 14: File I/O
- 1.28Module 14 File IO (Assignment Questions)1 Week
- 1.29Module 15: Object Oriented Programming
- 1.30Module 15 Object Oriented Programming (Assignment Questions)1 Week
- 1.31Module 16: Exception Handling
- 1.32Module 16 Exception Handling (Assignment Questions)1 Week
- 1.33Module 17: Regular Expressions (Regex)
- 1.34Module 17 Regular Expressions (Regex) (Assignment Questions)1 Week
- 1.35Python Quizzes1 Hour50 Questions
- SQL (Structured Query Language)23
- 2.1Module 1: SQL Basics
- 2.2Module 1 SQL Basics (Assignment Questions)1 Week
- 2.3Module 2: DML, DDL & DQL
- 2.4Module 2 DML, DDL & DQL (Assignment Questions)1 Week
- 2.5Module 3: SQL Constraints
- 2.6Module 3 SQL Constraints (Assignment Questions)1 Week
- 2.7Module 4: Querying Data
- 2.8Module 4 Querying Data (Assignment Questions)1 Week
- 2.9Module 5: SQL Joins
- 2.10Module 5 SQL Joins (Assignment Questions)1 Week
- 2.11Module 6: SQL Functions
- 2.12Module 6 SQL Functions (Assignment Questions)1 Week
- 2.13Module 7: Aggregate Functions and Grouping
- 2.14Module 7 Aggregate Functions and Grouping (Assignment Questions)1 Day
- 2.15Module 8: Subqueries and Nested Queries
- 2.16Module 8 Subqueries and Nested Queries (Assignment Questions)1 Week
- 2.17Module 9: Window Functions
- 2.18Module 9 Window Functions (Assignment Questions)1 Week
- 2.19Module 10: Indexing and Performance Optimization
- 2.20Module 10 Indexing and Performance Optimization (Assignment Questions)1 Week
- 2.21Module 11: Data Warehousing Concepts
- 2.22Module 11 Data Warehousing Concepts (Assignment Questions)1 Week
- 2.23SQL (Structured Query Language) Quizzes1 Hour50 Questions
- PYTHON LIBRARIES11
- 3.1Module 1: NumPy for Numerical Computing
- 3.2Module 1 NumPy for Numerical Computing(Assignment Questions)1 Week
- 3.3Module 2: Pandas for Data Manipulation
- 3.4Module 2 Pandas for Data Manipulation (Assignment Questions)1 Week
- 3.5Module 3: Data Visualization with Matplotlib
- 3.6Module 3 Data Visualization with Matplotlib (Assignment Questions)1 Week
- 3.7Module 4:Data Visualization with Seaborn
- 3.8Module 4 Data Visualization with Seaborn (Assignment Questions)1 Week
- 3.9Module 5: Practical Applications and Case Studies
- 3.10Module 5 Practical Applications and Case Studies (Assignment Questions)1 Week
- 3.11Python Libraries Quizzes1 Hour50 Questions
- STATISTICS11
- 4.1Module 1: Introduction to Statistics
- 4.2Module 1 Introduction to Statistics (Assignment Questions)1 Week
- 4.3Module 2: Understanding Population and Samples
- 4.4Module 2 Understanding Population and Samples (Assignment Questions)1 Week
- 4.5Module 3: Measures of Central Tendency and Dispersion
- 4.6Module 3 Measures of Central Tendency and Dispersion (Assignment Questions)1 Week
- 4.7Module 4: Probability and Probability Distributions
- 4.8Module 4 Probability and Probability Distributions (Assignment Questions)1 Week
- 4.9Module 5: Hypothesis Testing
- 4.10Module 5 Hypothesis Testing (Assignment Questions)3 Days
- 4.11Statistics Quizzes1 Hour50 Questions
- MACHINE LEARNING23
- 5.1Module 1: Introduction to Machine Learning
- 5.2Module 1 Introduction to Machine Learning (Assignment Questions)1 Week
- 5.3Module 2: Supervised Learning
- 5.4Module 2 Supervised Learning (Assignment Questions)1 Week
- 5.5Module 3: Unsupervised Learning
- 5.6Module 3 Unsupervised Learning (Assignment Questions)1 Week
- 5.7Module 4: Support Vector Machines (SVM)
- 5.8Module 4 Support Vector Machines (SVM) (Assignment Questions)1 Week
- 5.9Module 5: Decision Tree Classification
- 5.10Module 5 Decision Tree Classification (Assignment Questions)1 Week
- 5.11Module 6: Ensemble Learning
- 5.12Module 6 Ensemble Learning (Assignment Questions)1 Week
- 5.13Module 7: Model Selection Techniques
- 5.14Module 7 Model Selection Techniques (Assignment Questions)1 Week
- 5.15Module 8: Recommendation Systems
- 5.16Module 8 Recommendation Systems (Assignment Questions)1 Week
- 5.17Module 9: Text Analysis
- 5.18Module 9 Text Analysis (Assignment Questions)1 Week
- 5.19Module 10: Dimensionality Reduction
- 5.20Module 10 Dimensionality Reduction (Assignment Questions)1 Week
- 5.21Module 11: OpenCV
- 5.22Module 11 OpenCV (Assignment Questions)1 Week
- 5.23Machine Learning Quizzes1 Hour50 Questions
- Deep Learning & Neural Networks27
- 6.1Module 1: Introduction to Artificial Neural Networks
- 6.2Module 1 Introduction to Artificial Neural Networks (Assignment Questions)1 Week
- 6.3Module 2: Introduction to Deep Learning
- 6.4Module 2 Introduction to Deep Learning (Assignment Questions)1 Week
- 6.5Module 3: TensorFlow Basics
- 6.6Module 3 TensorFlow Basics (Assignment Questions)1 Week
- 6.7Module 4: Optimizers
- 6.8Module 4 Optimizers (Assignment Questions)1 Week
- 6.9Module 5: Activation Functions
- 6.10Module 5 Activation Functions (Assignment Questions)1 Week
- 6.11Module 6: Building Artificial Neural Networks
- 6.12Module 6 Building Artificial Neural Networks (Assignment Questions)1 Week
- 6.13Module 7: Modern Deep Learning Optimizers and Regularization
- 6.14Module 7 Modern Deep Learning Optimizers and Regularization (Assignment Questions)1 Week
- 6.15Module 8: Building Deep Neural Networks Using Keras
- 6.16Module 8 Building Deep Neural Networks Using Keras (Assignment Questions)1 Week
- 6.17Module 9: Convolutional Neural Networks (CNNs)
- 6.18Module 9 Convolutional Neural Networks (CNNs) (Assignment Questions)1 Week
- 6.19Module 10: Word Embedding
- 6.20Module 10 Word Embedding (Assignment Questions)1 Week
- 6.21Module 11: Recurrent Neural Networks (RNNs)
- 6.22Module 11 Recurrent Neural Networks (RNNs) (Assignment Questions)1 Week
- 6.23Module 12: Generative Adversarial Networks (GANs)
- 6.24Module 12 Generative Adversarial Networks (GANs) (Assignment Questions)1 Week
- 6.25Module 13: Speech Recognition APIs
- 6.26Module 13 Speech Recognition APIs (Assignment Questions)1 Week
- 6.27Deep Learning & Neural Networks Quizzes1 Hour50 Questions
- Capstone Project1
- Final Exam2


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