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Machine Learning Crash Course for Beginners

Machine Learning Crash Course for Beginners
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    Live Online Classes starting on 29th Jun 2024
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    Instructor-led Introduction to Machine Learning live online Training Schedule

    Flexible batches for you

    Price 14,99912,749
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    Starts at 4,250 / monthWith No Cost EMI Know more
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    Why enroll for Machine Learning Course?

    pay scale by Edureka courseThe global ML market size was valued at USD 38.11B in 2022 and is expected to hit USD 771.38B by 2032 at a CAGR of 37.3% from 2023 to 2032.
    IndustriesAI and ML are shaping the future of humanity across every industry and will continue to act as a technological innovator for the foreseeable future.
    Average Salary growth by Edureka courseAs per Glassdoor, the average annual salary for an ML Engineer in US is $165,099 with average additional cash compensation of $37,158.

    Machine Learning Crash Course Benefits

    Machine Learning market is projected to reach $771.38B by 2032 with salaries for ML professionals ranging from $80,000 to over $250,000 per year, multitude of opportunities are opening up for professionals seeking to build a career in this domain. As Machine learning is being integrated into various industries, learning this skill ensures individuals are equipped with future-proof capabilities that are in high demand across sectors.
    Annual Salary
    ML Research Engineer average salary
    Hiring Companies
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    Annual Salary
    Data Scientist average salary
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    Annual Salary
    ML Engineer average salary
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    Why Machine Learning Course from edureka

    Live Interactive Learning

    Live Interactive Learning

    • World-Class Instructors
    • Expert-Led Mentoring Sessions
    • Instant doubt clearing
    Lifetime Access

    Lifetime Access

    • Course Access Never Expires
    • Free Access to Future Updates
    • Unlimited Access to Course Content
    24x7 Support

    24x7 Support

    • One-On-One Learning Assistance
    • Help Desk Support
    • Resolve Doubts in Real-time
    Hands-On Project Based Learning

    Hands-On Project Based Learning

    • Industry-Relevant Projects
    • Course Demo Dataset & Files
    • Quizzes & Assignments
    Industry Recognised Certification

    Industry Recognised Certification

    • Edureka Training Certificate
    • Graded Performance Certificate
    • Certificate of Completion

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    About your Machine Learning Course

    Machine Learning Beginner Course Skills Covered

    • skillPython Programming
    • skillMachine Learning
    • skillTime Series Analysis
    • skillProblem Solving
    • skillAnalytics
    • skillData Visualization

    Tools Covered in Machine Learning Beginner Course

    •  tools
    •  tools
    •  tools
    •  tools
    •  tools
    •  tools
    •  tools

    Machine Learning Crash Course Curriculum

    Curriculum Designed by Experts

    AdobeIconDOWNLOAD CURRICULUM

    Introduction to Machine Learning with Python

    7 Topics

    Topics:

    • Need for Programming
    • Overview of Python
    • Machine Learning Fundamentals
    • Machine Learning Use Cases
    • Machine Learning Process Flow
    • Machine Learning Categories
    • Predictive ML Models

    skillHands-on:

    • 911 Call Data Analysis
    • Stock Market Analysis

    skillSkills you will Learn

    • Machine Learning Concepts
    • Machine Learning Types

    Supervised Machine Learning: Regression

    11 Topics

    Topics:

    • What is Linear Regression?
    • Why is Linear Regression Important?
    • Types of Linear Regression
    • What is the Best Line?
    • Assumptions of Simple Linear Regression
    • Assumptions of Multiple Linear Regression
    • Evaluation Metrics
    • Implementation of Linear Regression
    • Regularization Techniques for Linear Models
    • Polynomial Regression Model
    • Maximum Likelihood Estimation

    skillHands-on:

    • House Price Prediction
    • Customer Churn Prediction
    • Energy Consumption Prediction

    skillSkills you will Learn

    • Regression Concepts
    • Implementation of Regression Model

    Supervised Machine Learning: Classification

    12 Topics

    Topics:

    • What is Classification and its use cases?
    • What is a Decision Tree?
    • Algorithm for Decision Tree Induction
    • Creating a Perfect Decision Tree
    • What is Random Forest?
    • What is Naïve Bayes?
    • How Naïve Bayes works?
    • Implementing Naïve Bayes Classifier
    • What is a Support Vector Machine?
    • Illustrate how Support Vector Machine works.
    • Hyperparameter Optimization
    • Grid Search vs. Random Search

    skillHands-on:

    • Social Media Spam Detection
    • Credit Card Fraud Detection
    • Customer Segmentation

    skillSkills you will Learn

    • Supervised Learning concepts
    • Implementing various Supervised Learning algorithms

    Unsupervised Machine Learning

    7 Topics

    Topics:

    • What is Clustering & its Use Cases?
    • What is K-means Clustering?
    • How does the K-means algorithm work?
    • How to do optimal clustering
    • What is C-means Clustering?
    • What is Hierarchical Clustering?
    • How does Hierarchical Clustering work?
    • Recommendation Systems

    skillHands-on:

    • Music Recommendation System
    • Market Basket Analysis
    • Movie Recommendation System

    skillSkills you will Learn

    • Unsupervised Machine Learning Concepts
    • Implementation of Clustering Techniques

    Time Series Analysis

    10 Topics

    Topics:

    • What is Time Series Analysis?
    • Importance of TSA
    • Components of TSA
    • White Noise
    • AR model
    • MA model
    • ARMA model
    • ARIMA model
    • Stationarity
    • ACF & PACF

    skillHands-on:

    • Air Quality Index Prediction
    • Website Traffic Prediction
    • ECG Anomaly Prediction

    skillSkills you will Learn

    • TSA Forecasting in Python
    • TSA Anomaly Detection in Python

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    Machine Learning Introduction Course Description

    About the Machine Learning Crash Course for Beginners

    The Machine Learning Introduction Program for Beginners offers a comprehensive understanding of machine learning principles. Participants explore supervised and unsupervised techniques, including regression, classification, and clustering, through interactive discussions and practical examples. Additionally, insights into time series algorithms enable effective analysis of sequential data. With a focus on practical applications, learners gain valuable experience in implementing machine learning algorithms.

      What are the learning outcomes of this Machine Learning Crash Course for Beginners?

      • Understanding fundamental machine learning concepts.
      • Proficiency in supervised learning techniques like regression and classification.
      • Familiarity with unsupervised learning methods, particularly clustering.
      • Ability to analyze sequential data using time series algorithms.
      • Practical experience in implementing machine learning algorithms through real-world examples.
      • Strong grasp of the principles and applications of machine learning, enabling further exploration and advancement in the field.

      Who should take up this Machine Learning Introduction Course?

      The Machine Learning Introduction course is for those who want to fast-track their Machine Learning career. This Machine Learning Course will benefit the people working in the following roles:
      • Freshers
      • Data Science Professionals
      • Machine Learning Professionals
      • Analytics Professionals
      • Software Developers
      • Computer Science Students

      What are the prerequisites for this Machine Learning Crash Course?

      There are no prerequisites for enrollment in this Machine Learning Crash Course. Whether you are an experienced IT professional or an aspirant planning to enter the world of Machine Learning, this course is designed and developed to accommodate various professional backgrounds.

        What are the system requirements for this Machine Learning Crash Course for Beginners?

        The system requirements for the Machine Learning Course include:
        • A laptop or desktop computer with a minimum of 8 GB RAM and an Intel Core-i3 and above processor
        • A stable and high-speed internet connection is necessary for accessing online course materials, videos, and software
        • Python environment

        Machine Learning Beginner Course Projects

         certification projects

        Heart Disease Prediction

        This project aims to develop a machine-learning model capable of predicting the likelihood of heart disease in individuals based on various medical attributes. Leveraging dataset....
         certification projects

        Anomaly Detection in Network Traffic

        This project leverages Long Short-Term Memory (LSTM) networks, a type of recurrent neural network (RNN), to detect abnormal patterns in network data. LSTM networks are well-suite....

        Machine Learning Crash Course Certification

        To unlock the Edureka’s Machine Learning Crash Course completion certificate, you must ensure the following:

        • Completely participate in this Machine Learning Crash Course for Beginners Certification training course.

        • Evaluation and completion of the quizzes and projects listed.

        This Machine Learning Introduction Course enhances the value of your credentials by confirming your expertise in this fast-developing area. This certification showcases your adeptness in grasping machine learning concepts, which helps you apply the acquired knowledge in practice and highlights your credibility and attractiveness to the market, opening gateways for career growth in machine learning-related positions across industries.

        After obtaining the Machine Learning for Beginners certification, you may be qualified for a range of job roles. Some of the more specific job roles you may be qualified for include:

        • Machine Learning Engineer

        • Data Scientist

        • Machine Learning Researcher

        • Data Analyst

        • Business Intelligence Analyst

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        Machine Learning Crash Course FAQs

        What is Machine Learning?

        Machine learning is an integral component of data sciences' rapid expansion. Through statistical methods, algorithms are trained to make predictions or classifications and uncover vital insights for data mining projects, which then influence business and application decisions with positive impacts on key growth metrics. As more big data accumulates and expands exponentially, more data scientists will be needed to identify critical business questions and their answers within big data collections. There are several types of ML algorithms, including supervised learning, unsupervised learning, and reinforcement learning.

        What programming languages are commonly used in machine learning?

        Python is the most commonly used programming language for machine learning, along with libraries such as TensorFlow, PyTorch, and scikit-learn. R is also popular for statistical analysis and machine learning tasks.

        Will I get placement assistance after completing this Machine Learning Crash Course?

        To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the "create your resume" option.


        Who are the instructors for the Machine Learning Crash Course for Beginners?

        All the instructors at edureka are practitioners from the Industry with a minimum of 10-12 years of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants.

        What if I have more queries after completion of Machine Learning Crash Course for Beginners?

        Just give us a CALL at +91 98702 76459/1844 230 6365 (US Tollfree Number) OR email at sales@edureka.co.


        What if I miss a class of Machine Learning Crash Course for Beginners?

        You will never miss a lecture at Edureka! You can choose either of the two options:


        • View the recorded session of the class available in your LMS.

        • You can attend the missed session, in any other live batch.

        How long does it take to complete this Machine Learning Crash Course?

        The duration of the Machine learning crash course is 15 hours. The batches are scheduled on the weekend, i.e., Saturday and Sunday.

        Is it worth learning this Introduction to Machine Learning Course?

        In today's data-driven and automated world, machine learning emerges as an exceptionally rewarding and lucrative career choice. The demand for machine learning expertise has surged dramatically, with The World Economic Forum projecting a 40% increase in demand for AI and machine learning specialists from 2023 to 2027.

        Will I have lifetime access to the Machine Learning Crash course?

        Yes, once you enroll in the Machine Learning Crash course, you will have access for a lifetime.

        How much does this Machine Learning Crash Course cost?

        The Machine Learning Crash Course costs INR 14,999, but with a discount, you can get it for INR 12,749. You will also get a no-cost EMI option.

        What is the salary of a fresher in machine learning?

        According to Glassdoor, the average salary for a Machine Learning Engineer in India is ₹11,50,000 per year. 

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