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Certification Course in Machine Learning with Python

This is a Machine Learning with Python Certification Training Course from EarlyRise.

Machine learning is a subset of artificial intelligence that describes how software and applications can improve their efficiency and effectiveness in making predictions without being explicitly programmed to do so. In order to forecast future output, machine learning (ML) trains computers to integrate new algorithms into their processing power along with previous data.
In order to process information accurately without allocating specialised resources to get the same result, ML is finding its way into a wide range of industries and business of all kinds. As a result, professionals with coding expertise in this area are in high demand.

Machine Learning with Python Certification Training Course

Overview | Training Options | Curriculum | Certification | Why Machine Learning with Python Certification | FAQ's | Get In Touch

Machine Learning with Python Certification Course Overview

EarlyRise’s Machine Learning with Python Certification course has been created by industry professionals to help you to learn the Machine Learning with Python as per the industry requirements and demands. It gives you a solid foundation and will make you industry ready.

EarlyRise’s Machine Learning with Python training Course Key Features
  • Instructor led online classes conducted by industry experts
  • Simulation exams
  • Hands-On based ML with Python Training
Benefits

skill Real Time Projects

skill Expert Faculty

skill Enhanced Skills

skill Improved Efficiency

skill Ethical Awareness

skill Career Advancement

skill Access to Tools

skill Ongoing Support

Course info
  • Course Date : Coming Soon
  • Time : Coming Soon
  • Duration : 40 Hours
  • Levels : Beginner
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Training Options

ONLINE TRAINING

14,999
  • Learn in an instructor-led online training class
  • One to one mentorship for doubt resolution
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CLASSROOM TRAINING

19,999
  • Classroom based training
  • One to one mentorship for doubt resolution
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CORPORATE TRAINING CUSTOMIZED BASED ON YOUR REQUIREMENTS

Customized to your team's needs

  • Customized learning delivery model (self-paced and/or instructor-led)
  • Flexible pricing options
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Machine Learning with Python Training Course Curriculum

Eligibility

This course can be taken by any fresh graduates, software developers, infrastructure engineers, project managers, delivery heads, Systems operators, Cloud solutions architects, and DevOps engineers. However, professionals with knowledge of foundational python programming and statics will have an edge in understanding the concepts.

Pre-requisites

There are no Pre-requisites for this course. However, it would be more advantageous to have a basic understanding of python programming and statics in understanding the concepts.

Course Content

1. Fundamentals of Machine Learning: Introduces core concepts and algorithms, including supervised and unsupervised learning.
2. Python Programming for Data Science: Focuses on using Python libraries like NumPy, pandas, and scikit-learn for data manipulation and machine learning.
3. Data Preprocessing: Teaches techniques for cleaning, transforming, and preparing data for analysis and modeling.
4. Model Selection and Evaluation: Covers how to choose appropriate algorithms and evaluate model performance using metrics like accuracy, precision, and recall.
5. Feature Engineering: Includes methods for selecting and creating relevant features to improve model performance.
6. Algorithm Implementation: Provides practical experience with various machine learning algorithms, such as linear regression, decision trees, and clustering.
7. Hands-On Projects: Involves working on real-world projects to apply machine learning techniques and solve practical problems.
8. Project: Apply what you’ve learned in a final project.
9. Future Trends: Upcoming developments and career paths.

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Curriculum

Estimated Course Duration

40 Hours

Learners Commitment

8 hours per week

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  • Basics of Machine Learning
  • What and why Machine Learning
  • Applications of Machine Learning
  • Types of Machine Learning
  • Main Challenges of Machine Learning
  • Introduction to Scikit Learn
  • Features of Scikit Learn
  • Conventions
  • Implementation Steps
  • Vectors (2D,3D)
  • Dot Product
  • Hyperplane
  • Square, Rectangle
  • Hypercube
  • Data Types and its Measures
  • Random Variables,its Application with Variables
  • Probability Application with Examples
  • Probability Distribution with Examples
  • Sampling Funnel-why and how
  • What is Statistics
  • Basic Terminologies in Statistics
  • Types of Statistics
  • Descriptive Statistics
  • Measure of Central Tendency (MEAN, MEDIAN, MODE)
  • Measures of dispersion (Variance,Standard Deviation,Range-its derivation)
  • Measures of Skewness & kurtosis
  • Inferential Statistics
  • Is Your Data Clean?
  • What is Data Pre-processing?
  • Data cleaning Techniques
  • Introduction
  • 2D Scatter-plot
  • 3D Scatter-plot
  • Pair plots
  • Univariate, Bivariate and Multivariate
  • Histogram
  • Box-plot
  • Variance, Standard Deviation
  • Median
  • IQR ( InterQuartile Range)
  • Introduction
  • Need for Feature Engineering in Machine Learning
  • Steps in Feature Engineering
  • Feature Engineering Techniques
  • Confusion Matrix
  • ROC Curve
  • Cross Validation in Machine Learning
  • K fold Cross Validation & Grid search
  • Linear Regression - Mathematical Intuition
  • Programming of Linear Regression in Python-Scikit Learn
  • Cross Validation in Machine Learning
  • K fold Cross Validation & Grid search
  • Difference between Regression and Classification
  • Various Algorithms in Classification
  • Logistic Regression
  • Unsupervised Learning
  • Types of Unsupervised Learning
  • Applications of Unsupervised Learning
  • Introduction to Clustering Algorithms
  • Types of Clustering Algorithms
  • What is K-Means Clustering?
  • Implementation of K-Means Clustering
  • Improving Models
  • What is Association Rule Mining?
  • Algorithms in Association Rule Mining
  • Implementation of Apriori in Python

TOOLS TO COVER

certificate

Professional Certificate From EarlyRise

Upon successful completion of the course, participants will receive a certificate from EarlyRise. This certificate is widely recognized and signifies that the holder has acquired specialized skills and knowledge in Machine Learning with Python. It serves as a testament to their expertise and is valued by industry professionals and employers.

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Program Fee and Payment Method

Program Fee : Rs. 14,999 + 18% GST = Rs. 17,699

Candidates can pay the program fee through Netbanking, Credit/Debit cards, Cheque or DD

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Career Service

Mock Interview Preparation

EarlyRise has collaborated with industry experts to ensure you can get through the interview preparation just like the real ones.This service is free of cost for Cloud and Program.

Resume Building

Recommendation to make your resume stand out in the crowd. Qualitative feedback to customize your existing resume to nail the job you desire.

One on One Career mentoring

One-on-One sessions with personalized attention with highly experienced industry professionals to guide you on the career path that's just right for you. Precise suggestions on setting achievable short and long term goals.

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Why Machine Learning with Python Training from EarlyRise?

Industry Recognised Certification

EarlyRise Training Certificate

Certificate of Completion

Hands-On Project Based
Learning

Industry-Relevant Use Cases

Practical based training approach

Learn from experts active in their field

Leading industry professionals who bring current best practices and case studies to sessions that fit into your work schedule.

Nominal Course Fee

Our Course fees are very nominal and competitive. We provide Scholarship up to 50% time to time for eligible candidates.

FAQ's

All classes conducted by Expert Faculty and Industry Experts.

Yes, If you are looking for free resources then read our blogs and posts from EarlyRise.

Professionals seeking a good career can start learning this course.

Yes, sure. At the end of this course you will get a course completion certification from EarlyRise which is so beneficial for you.

Yes Definitely!
In between the course journey, you will be asked to do many assignments and homework related to your course and its useful for interview time.

Totally 40 hrs.
The total course duration will be 40 hrs but there is no rush to complete the course

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Salient Features of the Course

  • Covers fundamental to advanced machine learning concepts and techniques using Python.
  • Provides practical experience with real-world projects to apply learned skills and build a portfolio.
  • Focuses on key Python libraries such as scikit-learn, TensorFlow, and Keras for implementing machine learning algorithms.
  • Teaches essential techniques for cleaning, transforming, and preparing data for model training.
  • Includes training on constructing, evaluating, and tuning machine learning models.