With The AI & Machine Learning Offered By Liimrasoft Academy You Will Reach Greater Heights
Expert-Led AI & Machine Learning Course for Career Advancement
Gain practical knowledge and hands-on experience to harness the power of AI & Machine Learning for transformative solutions
Next Batch
Starts from: April 13, 2024
Duration: 60 Hours
Days: Sat & Sun
Timings: 10:00 AM to 12:30 PM CST
Course Overview
Explore the dynamic realm of Artificial Intelligence and Machine Learning with this intensive course led by industry expert Raghul Ramesh. Covering foundational concepts, Python for data science, statistical analysis, and advanced machine learning techniques, participants will gain hands-on experience in deep learning, natural language processing, and culminate their learning with a practical capstone project. With a focus on both theoretical understanding and practical application, this course is designed to empower professionals and enthusiasts alike in mastering the intricacies of AI and ML.
Highlights of AI & Machine Learning Training
Live Interactive Sessions
Job Course content developed by industry experts
Guided hands on exercise
60 Hrs Instructor Led Sessions
Capstone Project Workshop
On Demand Learning Sessions
2 Mockup Interviews By Industry Experts
Comprehensive Job Support
Resume Preparation By Industry Experts
Why Choose Us?
Who Should Attend This Training?
- Aspiring Data Scientists
- Data Analysts and Scientists
- Software Developers and Engineers
- Business Analysts
- Technology Enthusiasts
What You Will Learn?
- Foundational AI and ML Concepts
- Practical Python and Data Science Skills
- Statistical Analysis and Hypothesis Testing
- Machine Learning Algorithms and Evaluation: Explore a variety of supervised le
- Deep Learning and Advanced NLP
What You Will Get From That?
- Comprehensive Skill Set:
- Hands-On Experience
- Industry-Relevant Knowledge
- Course Materials and Resources
- Capstone Project and Mentorship
Course Content
Introduction to AI and Machine Learning
- Foundational Concepts: Explore the basic principles and foundational concepts of Artificial Intelligence and Machine Learning.
- ML Lifecycle Overview: Understand the end-to-end Machine Learning lifecycle, covering data preparation, model training, and deployment.
- Tools and Environments: Familiarize yourself with essential tools and environments, including Python and Jupyter Notebooks, for practical implementation.
Python for Data Science
- Python Basics: Cover the fundamental aspects of Python programming, including data types, loops, and functions.
- Libraries (NumPy, Pandas): Introduce and apply data science libraries like NumPy and Pandas for efficient data manipulation and analysis.
- Data Manipulation and Analysis: Utilize Python and data science libraries to manipulate and analyze datasets effectively.
Statistics for Machine Learning
- Descriptive Statistics and Probability: Learn descriptive statistics and probability to lay the statistical foundation for machine learning.
- Inferential Statistics: Delve into inferential statistics, enabling predictions and insights from sample data.
- Hypothesis Testing and Experimentation: Explore hypothesis testing techniques and methodologies for experimentation in machine learning.
Data Preprocessing
- Data Cleaning and Preprocessing Techniques: Master techniques for cleaning and preprocessing data to ensure quality for machine learning applications.
- Feature Engineering and Selection: Understand the significance of feature engineering and selection to optimize datasets for model performance.
- Data Visualization with Matplotlib and Seaborn: Learn data visualization using Matplotlib and Seaborn for effective communication of insights.
Machine Learning Fundamentals
- Supervised Learning Algorithms: Dive into supervised learning, covering algorithms such as Linear Regression and Logistic Regression.
- Evaluation Metrics: Explore key evaluation metrics like accuracy, precision, and recall for assessing model performance.
- Unsupervised Learning Introduction: Gain an introduction to unsupervised learning, focusing on clustering techniques.
Advanced Machine Learning
- Decision Trees and Random Forests: Explore decision trees, random forests, and ensemble methods for advanced machine learning.
- Support Vector Machines: Understand the principles and applications of Support Vector Machines (SVM) in machine learning.
- Ensemble Methods and Boosting Techniques: Dive into ensemble methods and boosting techniques for enhancing model performance.
Introduction to Deep Learning
- Neural Network Basics: Cover the fundamentals of neural networks as a foundation for deep learning.
- Implementing a Basic Neural Network: Gain hands-on experience in implementing a basic neural network using TensorFlow/Keras.
- Understanding Loss Functions and Optimizers: Explore the concepts of loss functions and optimizers in the context of neural networks.
Convolutional Neural Networks (CNNs)
- CNNs for Image Recognition: Understand the application of Convolutional Neural Networks (CNNs) in image recognition.
- Implementing a CNN: Gain practical experience by implementing a CNN using TensorFlow/Keras.
- Data Augmentation Techniques: Explore data augmentation techniques to enhance the robustness of image recognition models.
Recurrent Neural Networks (RNNs) and NLP
- RNNs and Sequence Modeling: Explore Recurrent Neural Networks (RNNs) and their applications in sequence modeling.
- Introduction to Natural Language Processing (NLP): Gain an understanding of Natural Language Processing (NLP) and its significance in machine learning.
- Text Processing and Tokenization Techniques: Learn essential text processing and tokenization techniques for NLP.
Advanced NLP and Transformers
Advanced NLP Concepts: Dive into advanced NLP concepts, including word embeddings and attention mechanisms.
Introduction to Transformers and BERT: Understand the fundamentals of transformers and BERT (Bidirectional Encoder Representations from Transformers) in NLP.
Implementing a Transformer Model: Gain hands-on experience by implementing a transformer model for text classification.
Capstone Project Introduction
Overview of Capstone Project: Understand the guidelines, expectations, and objectives of the capstone project.
Ideation, Team Formation, and Project Planning: Collaborate on ideation, form teams, and plan the execution of the capstone project.
Capstone Project Workshop
Capstone Project Work: Engage in the practical implementation of the capstone project, applying learned skills in a real-world scenario.
Mentorship and Troubleshooting: Receive mentorship and troubleshooting support to ensure successful completion of the capstone project
Our AI & Machine Learning Trainer Profile
Raghul Ramesh
Raghul Ramesh, an industry veteran with over 17 years of rich experience in Information Technology, boasts a formidable 14-year expertise specifically in the realm of Artificial Intelligence. With a proven track record, Raghul has successfully navigated and contributed to diverse sectors, including banking and finance, insurance, pharmaceuticals, e-commerce, and manufacturing. His extensive background in these industries provides a unique perspective, allowing him to contextualize AI and machine learning concepts with real-world applications. Raghul’s training approach is enriched by his hands-on experience, ensuring that participants not only grasp theoretical concepts but also glean insights into the practical implementation of AI and ML in various business domains.
Course Prices
Online Training
- Comprehensive Customized Curriculum
- Hands-On Labs and Projects
- Industry-Expert Instructors
- Access to Training Material
- 100% Money Back Guaranteed
- Best Price Guaranteed in the Training Industry
Bootcamp
- Coming Soon
Corporate Training
Customized to your team's needs
- Comprehensive Customized Curriculum
- Hands-On Labs and Projects
- Industry-Expert Instructors
- Access to Training Material
- 100% Money Back Guaranteed
- Best Price Guaranteed in the Training Industry
Frequently Asked Questions
1What if I miss an Online Session?
We ensure that you never miss a class. In case you do, you have two options:
-Access the recorded sessions provided to you regularly.
-Attend the live session of the same topic in another batch.
2What if I have any Questions after completion of my course?
There's no need for concern. Upon joining any course with us, you'll receive ongoing support from our dedicated team, which is available round-the-clock to assist you.
3What is meant by Online Training?
Instructor led online interactive sessions
4Will I get any discount on the course?
Our course fee is already discounted price
5Do I have access to the course material after completing my training?
Upon enrolling with us, you will receive access to the course materials.
6What are the modes of training ?
Online instructor led & Bootcamp
7Will get a chance to switch from self-paced videos to live sessions?
Yes, you are eligible for this option. To participate, simply make the additional payment and join the live sessions.
8Our Refund policy?
No refund once attended
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