Best Artificial Intelligence and Machine Learning Course
Artificial Intelligence and Machine Learning Courses Online
Artificial Intelligence and Machine Learning are the most popular technologies contributing to the global digital transformation. Join Artificial Intelligence and Machine Learning Courses and become an Artificial Intelligence Engineer to get way to an exciting, developing profession.
About Artificial Intelligence and Machine Learning Course
(Instructor-Led Online Training)
Artificial Intelligence is a broader concept of machines depicting humans and carrying out smart tasks easily, whereas Machine Learning is its subset maximizing the performance of a machine. The combined study of it makes you familiar with the technologies incorporated and their importance today and in the future.
At the very beginning of our Artificial Intelligence and Machine Learning courses, we will understand AI/ML and its relevance to networking, use of python in AI/ML, and fundamental of AI/ML.
Then you will be introduced to the Language Models (LMs), Predictive AI, and Generative AI adding core practical exposure to your skills on how AI and ML-based projects are implemented in organizations.
So, if you are someone seeking a career as an Artificial Intelligence Engineer, our training is the best choice for you. Any knowledge of Programming or advanced mathematics isn’t compulsory to join the AI and ML Courses, so anyone interested in learning and innovating in the field of automation can enroll with us.
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Upcoming Batches Are Now Open!
BATCH
TIME
SEATS LEFT
Batch 1
Weekends Batch
(Saturday & Sunday)
15th March 2025 onwards
For 8 Weeks1 PM to 4 PM Indian Time
4 Seats
Batch 2
Weekends Batch
(Saturday & Sunday)
12th April 2025 onwards
For 8 Weeks5 PM to 8 PM Indian Time
10 Seats
Grab the Full Course Details
ENQUIRE NOW
READY TO LEVEL UP?
Upcoming Batches Are Now Open!
DATE
Batch 1
Weekends Batch
(Saturday & Sunday)
TIME
15th March 2025 onwards
For 8 Weeks1 PM to 4 PM Indian Time
SEATS LEFT
4 Seats
DATE
Batch 2
Weekends Batch
(Saturday & Sunday)
TIME
12th April 2025 onwards
For 8 Weeks5 PM to 8 PM Indian Time
SEATS LEFT
10 Seats
Grab the Full Course Details
ENQUIRE NOW
COURSE OUTLINE
AI and ML Courses (40 Hours)
Module 1
Module 2
Module 3
Module 4
Module 5
Module 6
Module 7
Module 1
Introduction to AI/ML and Its Relevance to Networking
Overview of AI and ML
- Definition and key concepts
- History and evolution of AI and ML
- Differences between AI, ML, and Deep Learning
AI and ML in the Networking Domain
- Importance of AI and ML in modern networks
- Use cases: Traffic prediction, anomaly detection, network optimization
Basic Concepts of Networking
- Review of essential networking concepts relevant to AI/ML
- The relationship between network data and machine learning
Module 2
Python for AI/ML and Networking
Introduction to Python
- Overview of Python and its use in AI/ML
- Python libraries for data science: NumPy, Pandas, Matplotlib
- Python libraries for network automation: Netmiko, Ncclient, Requests
Working with Network Data
- Parsing and analyzing network logs
- Basic data manipulation techniques with Pandas
Module 3
Fundamentals of Machine Learning
Understanding Machine Learning
- Supervised vs. Unsupervised learning
- Key algorithms: Linear regression, decision trees, k-means clustering
Feature Engineering for Network Data
- Extracting meaningful features from network logs
- Preprocessing data: Normalization, handling missing values
Module 4
Fundamentals of AI in Networking
Overview of Artificial Intelligence (AI)
- What is AI? Core concepts and historical context
- Types of AI: Narrow AI, General AI, and Superintelligent AI
- AI’s role in modern networking
AI Use Cases in Networking
- Network monitoring and optimization
- AI-powered predictive maintenance
Introduction to AI Techniques for Network Engineers
- Rule-based systems vs. machine learning in networking
- Overview of decision-making algorithms for automation
Module 5
Fundamentals of Language Models and AI
Introduction to Language Models (LMs):
- What are language models (LMs), and how do they work?
- The architecture behind LMs: Large Language Models (LLMs), n-grams, RNNs, and Transformers
- The importance of large-scale datasets for training LMs
Creating Language Models:
- Overview of the process to train language models
- Fine-tuning LMs for specific use cases
Applications of Language Models in Networking:
- Automated log analysis, chatbots for network support
- AI-driven configuration writing using natural language inputs
Module 6
Introduction to Predictive AI for Networking
What is Predictive AI?
- Predictive analytics and machine learning
- How predictive AI differs from traditional machine learning
Network Data for Predictive AI
- Collecting and processing network data
- Feature selection and engineering
Predictive AI Use Cases in Networking
- Traffic prediction
- Network failure forecasting
- Load balancing optimization
Module 7
Generative AI and its Application in Network Engineering
Introduction to Generative AI
- What is Generative AI?
- Overview of Generative Adversarial Networks (GANs) and Transformer models
- Generative AI’s role in simulating network environments
Generative AI for Network Configuration and Scripting
- Automated generation of network scripts
- AI-driven configuration templates for complex networks
Lab Outline
- Installing Python, VSCode, Jupyter Notebook, and necessary libraries
- Basic scripting and automation with Python and Ansible
- Data manipulation using sample network data collected from Cisco IOS devices
- Automating simple tasks on Cisco IOS and IOS XE using AI
- Using Scikit-learn for network data analysis
- Hands-on with linear regression and clustering on network data
- Using Scikit-learn to build predictive models for traffic patterns
- Using historical network data to predict future performance
- Applying predictive models to Cisco IOS XE and NSO environments for network automation
- Using generative AI to create network automation scripts for Cisco IOS XE and NSO
- Applying generated configurations to real networks for dynamic and adaptive network setups
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What is AI and ML course training?
Artificial Intelligence is the study of making computers do tasks that at present humans do better like Driving a Car, Playing Chess, Assisting and more. Whereas, Machine Learning is an application of AI that gives the ability to machines to learn on their own, without being explicitly programmed and improve performance through past experiences.
Artificial Intelligence and Machine Learning Course is designed for everyone who wants to learn and innovate in the field of automation. This training makes you familiar with AI and ML popular technologies and their importance today and in the future.
The Beginner level of AI and ML Courses deal with the conceptual understanding of the fundamentals of Artificial Intelligence and Machine Learning concepts. In this Foundation-level training, you learn about AI and ML applications and their real-life use cases in different industries, including banking, healthcare, automation, e-commerce etc.
Additionally, you get core practical exposure on how AI and ML based projects are implemented at organizations under expert’s guidance of experienced industry mentors.
Even if you are a professional with a non-technical background, you can get hands-on with Artificial Intelligence & Machine Learning experience without any knowledge of Programming.
Key Objectives of AI and ML Course
- To make you understand Artificial Intelligence and key components of ML model.
- Evaluating and Interpreting machine learning algorithm types.
- Developing basic Supervised and Unsupervised learning models.
- Understanding how to apply various methods to test Machine Learning training models.
- Makes you able to work on application development projects based on machine learning at your organization.
Who can attend AI and ML Course?
The AI and Machine Learning course is designed for all those who are interested in learning AI and ML techniques in the big data domain and write intelligent applications.
The most common attendees of this course are Higher Management employees, Developers & Engineers starting work on AI and ML projects.
Prerequisites for AI and ML Course
Curiosity to learn Artificial Intelligence and Machine Learning.
Frequently Asked Questions
Q1. Is their any Cisco Certification for AI and ML?
Cisco will now offer a new elective for its CCDE (Cisco Certified Design Expert) certification focused on AI infrastructure validating the skills of experienced Network Engineers in designing data center networks that can handle the demanding needs of AI workloads.
The very first time, CCDE AI Infrastructure elective will be available for testing is on February 9, 2025 at Cisco Live.
Q2. Does AI/ML skills offer high-paying job roles?
Some of the common job roles you get after AI and ML Course are – Machine Learning Engineer, Data Scientist, AI Research Scientist, AI/ML Architect, and Computer Vision Engineer. And, yes, they are considered high-paying due to the specialized skills required and the growing demand for professionals in these fields.
Q3. How can AI and ML Training help me?
If you are a Network Engineer, this training will help you in:
- Implementing different AI/ML use-cases and minimize the burden on infrastructure resources
- Building high-performance generative AI network fabrics
- Ensuring the security, sustainability and compliance of networks
- Making appropriate trade-offs between cost and power
- Matching compute power and cloud needs to measure carbon use
Q4. Which Cisco products use AI and ML?
Cisco products that leverage AI and ML for enhanced network performance, security, and management include:
- Cisco Catalyst Center (DNA Center)
- Cisco Nexus Dashboard Insights (NDI)
- Cisco Meraki
- Cisco AppDynamics
- Cisco ThousandEyes
- Cisco Secure Network Analytics
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