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One Day Course In Introduction To Machine Learning

Course Overview: The Introduction to Machine Learning course provides a foundational understanding of machine learning concepts, techniques, and applications. Throughout this engaging program, you will explore key topics such as supervised and unsupervised learning, algorithms, model evaluation, and feature engineering. You'll gain hands-on experience with popular machine learning tools and frameworks, empowering you to start building your own models. Key Topics Covered: Basics of machine learning and its importance Types of machine learning: supervised vs. unsupervised Common algorithms and their applications Model evaluation techniques and performance metrics Practical exercises using popular libraries (e.g., Scikit-learn, TensorFlow) Target Audience: This course is ideal for beginners, data enthusiasts, and professionals looking to understand the fundamentals of machine learning. No prior programming or statistical knowledge is required. Join us to kickstart your journey into the world of machine learning

Beginner 5(44 Ratings) 0 Students enrolled English
Created by Admin s
Last updated Sat, 21-Sep-2024
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Course overview

Mercury Mentors is dedicated to helping students build their careers by offering affordable, high-quality courses designed to equip them with essential skills and knowledge. By providing access to expert instructors and a focused curriculum at a low cost, Mercury Mentors ensures that students can enhance their employability without financial burden. The platform fosters a supportive learning environment, enabling students to network with peers and industry professionals, gain practical insights, and develop competencies that are highly valued in the job market. This commitment to accessible education empowers students to take significant steps toward achieving their career goals.

Course Overview: Welcome to the "Introduction to Machine Learning" course, a comprehensive 6-hour program designed to immerse you in the essential concepts and techniques of machine learning (ML). As a transformative field in technology and data science, machine learning empowers systems to learn from data and make informed predictions or decisions. This course is ideal for beginners and those looking to understand how ML can be applied across various industries.

Course Objectives: By the end of this course, participants will be able to:

  1. Understand the fundamental concepts and terminologies of machine learning.
  2. Differentiate between supervised and unsupervised learning.
  3. Identify common machine learning algorithms and their applications.
  4. Evaluate model performance using various metrics.
  5. Implement basic machine learning models using popular libraries.
  6. Recognize the ethical considerations and limitations of machine learning.

Course Outline:

1. Introduction to Machine Learning (1 hour)

  • What is Machine Learning? Definition and Scope
  • The Importance of Machine Learning in Today’s World
  • Overview of Machine Learning Applications (e.g., healthcare, finance, marketing)
  • Key Terminologies: Features, Labels, Models, and Training Data

2. Types of Machine Learning (1 hour)

  • Supervised Learning: Definition and Examples
    • Algorithms: Linear Regression, Decision Trees, Support Vector Machines
    • Use Cases: Classification and Regression Tasks
  • Unsupervised Learning: Definition and Examples
    • Algorithms: K-Means Clustering, Hierarchical Clustering, Principal Component Analysis
    • Use Cases: Data Exploration, Anomaly Detection

3. The Machine Learning Workflow (1 hour)

  • Understanding the ML Pipeline: From Data Collection to Deployment
  • Data Preprocessing: Cleaning, Normalizing, and Transforming Data
  • Feature Engineering: Selecting and Creating Features
  • Splitting Data: Training, Validation, and Test Sets

4. Model Evaluation and Selection (1 hour)

  • Evaluating Model Performance: Accuracy, Precision, Recall, F1 Score
  • Understanding Overfitting and Underfitting
  • Cross-Validation Techniques
  • Selecting the Right Model for Your Problem

5. Hands-On Session: Building Your First Machine Learning Model (1.5 hours)

  • Introduction to Popular Libraries: Scikit-learn, Pandas, Matplotlib
  • Practical Exercise: Building a Supervised Learning Model
    • Data Loading and Preprocessing
    • Model Training and Evaluation
    • Visualizing Results

6. Ethical Considerations in Machine Learning (30 minutes)

  • Understanding Bias in Machine Learning Models
  • The Importance of Fairness, Accountability, and Transparency
  • Real-World Examples of Ethical Challenges in AI and ML

7. Q&A and Wrap-Up Session (30 minutes)

  • Open Floor for Questions and Discussion
  • Resources for Further Learning in Machine Learning
  • Summary of Key Concepts Covered in the Course

Target Audience: This course is suitable for beginners, data enthusiasts, business analysts, and professionals from various fields looking to understand the basics of machine learning. No prior programming or statistical knowledge is required, making it accessible for all learners.

Learning Materials: Participants will receive access to course slides, practical exercises, a list of resources for further study, and recommended reading materials to deepen their understanding of machine learning concepts.

Conclusion: Join us for this engaging and informative course to kickstart your journey into the world of machine learning. By the end of the session, you will be equipped with essential skills and knowledge to begin exploring machine learning applications, empowering you to leverage data in innovative ways. Embrace the future of technology and enhance your career prospects in the exciting field of machine learning

Why Enroll?

 Networking Opportunities: Connect with industry professionals and peers.

 Resource Materials: Access exclusive readings and materials.

 Certificate of Completion: Enhance your resume with a recognized credential.

 Q&A Session: Engage directly with experienced practitioners.

 FollowUp Support: Discover further learning and career opportunities in the field.

7. Get access 650+ HR's email ID's hiring


What will i learn?

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Admin s

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Reviews

  • OGZFPdClyKbw WEqCtFGS
    The Machine Learning course was exceptional! It significantly enhanced my resume.
  • HhAqjVwfmXugsi vDXdVKPAGJbhHZ
    I gained practical skills that I can showcase on LinkedIn effectively.
  • qkTKyvUYXmzMx eCObjZIlNLdUvkPp
    Mock interview sessions focused on ML concepts, boosting my confidence for job applications.
  • uZKJkUjYedqEStD RGgrUoMNlKE
    Understanding algorithms and models improved my coding abilities tremendously.
  • QinNbBrIhTR kPOlRELVa
    The course clarified essential topics like regression and classification, now highlighted on my resume.
  • CkwyXMHSE gYdmVCSTURL
    Networking with fellow participants expanded my professional connections in data science.
  • JsMSgrLxE coJLitAahGKWRgFx
    The instructors were knowledgeable and provided real-world examples that made learning engaging.
  • AjoVMpFi aIcEUYWSitqHG
    Hands-on projects reinforced my understanding of machine learning applications.
  • LindaUnidoHR LindaUnidoHR
    I learned to use popular ML tools like TensorFlow, which enhances my LinkedIn profile.
  • sIHZrORjBYdwWo OegxoslpMKC
    This training provided a solid foundation in supervised and unsupervised learning.
  • qgCbhELjGsoc JcWEMCYBNw
    The emphasis on best practices in model evaluation was particularly beneficial.
  • XDyMuhrBwGVbAEdj SNRFTUIVCwAmln
    I updated my LinkedIn profile to reflect my new machine learning skills.
  • HenryPiodyEG HenryPiodyEG
    The course covered the latest trends in AI and machine learning effectively.
  • LzaWJSRIXeyZTxf qsGhOprLmnBtkZ
    I feel much more prepared for data science roles after completing this course.
  • cZOHxwdGoaqITr jtKyUNwdkJe
    Mock interviews included relevant ML questions that helped me practice effectively.
  • UGXkMAofmiRu yPUnuAFH
    Learning about feature engineering was a critical skill I gained from this course.
  • MartinSofXR MartinSofXR
    The interactive discussions encouraged participation and made learning enjoyable.
  • MichaelkemIV MichaelkemIV
    I received constructive feedback that helped refine my machine learning techniques.
  • MichaelkemIV MichaelkemIV
    The course taught me how to handle real datasets efficiently.
  • SfIQbPoV irfWhYHVzMXGg
    Understanding model deployment improved my project management skills.
  • sRSgUdiF HILjOlRJcoxQZbp
    This course is an excellent addition to my professional development plan.
  • dvThzpbJX maxKoPltzviU
    The hands-on labs were crucial for applying what I learned in real scenarios.
  • AkrVuUsZOJQbhmlK mdxwHfgEpkqyNSRU
    I now feel more confident in implementing machine learning solutions.
  • VxUYOBLP CIXENDJruhfB
    The trainers were experienced professionals who shared valuable industry insights.
  • vnSlUgfLtpB nQxMCFGg
    I learned how to use Git for version control in ML projects.
  • Rutuja 7620448903
    The course helped me develop a better understanding of data preprocessing techniques.
  • ymKTHPOpctsYjh gdaNQynHbASjZuTh
    The focus on ethical considerations in AI was enlightening and necessary.
  • izEqZaFSgO oqbRlImsTwk
    I found the discussions on neural networks particularly informative.
  • xKSkouwFaMXfTvmY CNmoQpDawTVn
    This course has truly prepared me for a successful career in machine learning.
  • MichaelkemIV MichaelkemIV
    The course emphasized the importance of data quality in machine learning projects.
  • MichaelkemIV MichaelkemIV
    I gained knowledge of various ML frameworks, enhancing my overall skill set.
  • ZmtUwSVcLq NluFSOyV
    The course provided valuable resources for further learning and exploration.
  • OwhfQyWLIgRuNAtV syfSKQUhbwXIpFvm
    I feel equipped to tackle machine learning challenges in real-world scenarios.
  • Divya 8925691008
    The collaborative projects helped me build teamwork skills essential for tech environments.
  • StevenhetTJ StevenhetTJ
    I appreciated the focus on practical applications, making the concepts relatable.
  • shfcGMkqjAZ IqZBfdEwbkpL
    The mock project presentations improved my communication skills significantly.
  • RaymondkafKL RaymondkafKL
    I learned how to effectively evaluate model performance using metrics.
  • ktCXSjEw zVEcBNHpiFmCb
    This course was a game-changer for my career in tech.
  • Sukhada 7057253266
    Overall, the Machine Learning course exceeded my expectations and enhanced my career prospects.
  • Madhavi Laxmi
  • Manju Devi
  • Leena Priya
  • Aryan Dev
  • Rishi Kumar
199₹
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