Transform Your Career with ENCODE-IT’s Artificial Intelligence (AI) Course

Artificial Intelligence (AI) is no longer a futuristic concept; it is revolutionizing industries today, from
healthcare and finance to e-commerce and entertainment. With its ability to automate complex
processes, make predictions, and improve decision-making, AI is one of the most exciting and rapidly
evolving fields in technology. ENCODE-IT’s Artificial Intelligence course is designed to equip you
with the necessary skills to build AI applications and algorithms that will drive innovation and
efficiency in real-world businesses.

Whether you're a beginner or looking to enhance your expertise in AI, this course provides in-depth
coverage of AI concepts, tools, and techniques. You’ll gain hands-on experience in machine learning,
neural networks, natural language processing (NLP), and deep learning. With a comprehensive
curriculum and practical applications, this course will prepare you for a successful career in AI and
machine learning.

Course Overview
The Artificial Intelligence (AI) course at ENCODE-IT is a beginner-friendly yet advanced-level
program that covers everything from the foundations of AI to the development of complex AI
algorithms. The course blends theoretical learning with practical implementation using popular AI
frameworks such as TensorFlow, Keras, and PyTorch. You will be introduced to core AI concepts like
machine learning, reinforcement learning, neural networks, and natural language processing, and
learn how to apply them to real-world problems.

By the end of this course, you will have the expertise to build and deploy AI-driven solutions for
businesses, optimize models, and contribute to cutting-edge AI research. This program is ideal for
aspiring AI professionals, software developers, and anyone interested in mastering the principles of
Artificial Intelligence.

Salary Scale in India
AI professionals in India are in high demand, and as the sector continues to grow, the need for
skilled AI engineers and data scientists is expected to rise even further. The average salary for an
entry-level AI engineer in India is typically between ₹6 lakh to ₹12 lakh annually. With 2-5 years of
experience, AI professionals can expect a salary range of ₹12 lakh to ₹20 lakh per year. Experienced
AI experts or data scientists with specialized skills can earn upwards of ₹20 lakh to ₹40 lakh, making
it a highly rewarding career choice.

Placement Assistance & Certification in India
ENCODE-IT’s AI course offers placement assistance to ensure you successfully transition into the
workforce. Our placement services include resume building, mock interviews, and job referrals.
Upon completing the course, you will receive a Certificate of Completion from ENCODE-IT, which is
recognized by top tech companies. This certification will help demonstrate your skills and enhance
your employability in the competitive AI job market.

Course Curriculum

1. Introduction to Artificial Intelligence
o What is Artificial Intelligence? A Historical Overview
o Key Areas of AI: Machine Learning, Neural Networks, Natural Language Processing
o AI Terminology and Basic Concepts
o Applications of AI in Various Industries (Healthcare, Finance, Automation)
o AI Tools and Frameworks Overview: TensorFlow, Keras, PyTorch

2. Python for AI Development
o Introduction to Python Programming for AI
o Working with Python Libraries: Numpy, Pandas, Matplotlib
o Data Structures and Algorithms for AI
o Python for Machine Learning and Data Manipulation
o Setting up Python for AI Projects (Jupyter Notebooks, IDEs)

3. Introduction to Machine Learning
o Machine Learning Fundamentals: Supervised, Unsupervised, and Reinforcement
Learning
o Types of Machine Learning Algorithms: Linear Regression, Logistic Regression,
Decision Trees
o Training and Testing Models with Scikit-Learn
o Overfitting, Underfitting, and Model Evaluation Metrics
o Cross-Validation and Hyperparameter Tuning

4. Neural Networks and Deep Learning
o Introduction to Neural Networks: Perceptron, Layers, and Activation Functions
o Building Neural Networks with Keras and TensorFlow
o Backpropagation and Gradient Descent Optimization
o Convolutional Neural Networks (CNN) for Image Recognition
o Recurrent Neural Networks (RNN) for Sequence Prediction
o Transfer Learning and Fine-Tuning Pre-trained Models

5. Natural Language Processing (NLP)
o Introduction to NLP: Text Processing, Tokenization, Lemmatization
o Text Classification, Sentiment Analysis, and Named Entity Recognition
o Text Vectorization: Bag of Words, TF-IDF, Word2Vec

o Building NLP Models with Python (spaCy, NLTK)
o Deep Learning for NLP: Transformers, BERT, GPT
o Speech Recognition and Text Generation

6. Reinforcement Learning (RL)
o Introduction to Reinforcement Learning: Agents, Environment, Rewards
o Key RL Algorithms: Q-Learning, Deep Q-Networks (DQN), Policy Gradient Methods
o Markov Decision Processes (MDP) and Bellman Equations
o Solving Real-World Problems with RL (Robotics, Gaming)
o Implementing RL in Python using OpenAI Gym and TensorFlow

7. AI for Computer Vision
o Introduction to Computer Vision and Image Processing
o Image Classification, Object Detection, and Segmentation
o Convolutional Neural Networks (CNN) for Image Analysis
o Preprocessing and Augmentation of Image Data
o Object Tracking and Face Recognition using OpenCV
o AI for Video Analysis and Scene Understanding

8. AI Ethics and Bias
o Understanding the Ethical Implications of AI and Automation
o Bias in AI Models and Mitigation Techniques
o Fairness, Accountability, and Transparency in AI Systems
o Privacy Concerns in AI: Data Privacy, GDPR, and Regulations
o Responsible AI: Building AI Systems that Benefit Society

9. Deploying AI Models
o Model Deployment Overview: From Development to Production
o Tools for Deploying AI Models: Flask, Django, TensorFlow Serving
o Creating AI-powered APIs and Web Apps
o Scaling AI Solutions with Cloud Platforms: Google Cloud, AWS, Azure
o Monitoring and Maintaining Deployed AI Models

10. Real-World AI Projects
o Building a Face Recognition System with Deep Learning
o Sentiment Analysis using NLP and Social Media Data

o AI-based Image Classification with CNN
o Predictive Analytics with Machine Learning Models
o AI in Healthcare: Disease Prediction using Machine Learning
o Real-Time Chatbot Development with NLP and AI

11. Final Project and Certification Exam
o Final Project: Build an AI Application from Scratch
o Implement AI Models for Real-World Problem Solving
o Final Exam: Comprehensive Evaluation of AI and Machine Learning Skills
o Certification of Completion from ENCODE-IT and Job Placement Assistance

Key Features
 Tools & Platforms: Python, TensorFlow, Keras, PyTorch, OpenCV, NLTK, spaCy, Scikit-Learn
 Real-World Projects: Work on industry-specific AI projects such as sentiment analysis, image
classification, predictive analytics, and chatbots.
 Expert Instructors: Learn from seasoned professionals with deep expertise in AI and
machine learning.
 Placement Support: Job referral, resume building, and mock interviews to help you land
your dream AI role.
 Comprehensive Curriculum: From the basics of AI to advanced deep learning and NLP
techniques, this course covers all essential AI topics.
 Career Advancement: Acquire in-demand AI skills for roles in machine learning engineering,
data science, and AI research.

With ENCODE-IT’s Artificial Intelligence course, you’ll unlock the potential to revolutionize
industries, drive innovation, and build intelligent systems that solve real-world problems. Join today
to take the first step toward a rewarding career in the fast-growing field of AI!