How to Learn Machine Learning: A Beginner’s Path

Machine learning can be exciting and challenging. Beginners can explore the diverse field with a disciplined approach and build a solid foundation. Here’s a beginner’s guide to setting foot in the world of machine learning.

Table of Contents:

• A Beginner's Guide
• The Most Upskilling Programs
• Conclusion

A Beginner’s Guide

Step 1: Grasp the Basics 

Before diving into machine learning courses, it’s essential to understand the basic concepts like the fundamentals of programming, preferably in Python, basic statistics and mathematics, linear algebra and calculus.

Step 2: Explore Online Resources 

Coursera, edX, and Udacity provide basic and advanced courses by renowned university and IT company professionals. 

Step 3: Hands-On Practice 

Theory is essential, but machine learning is practical. Work with Kaggle datasets. You may use what you've learned and build a portfolio of your abilities. 

Step 4: Delve Into Specialized Areas 

Once you have a handle on the basics, consider specializing. Areas like big data analytics training can complement your machine learning skills. 

Step 5: Join a Community 

Join forums, attend meetups, and participate in hackathons. Engaging with a community can provide support, inspiration, and opportunities for collaboration.

Step 6: Keep Learning 

Stay updated with the latest trends, techniques, and technologies. Follow thought leaders, read research papers, and never stop learning.

The Most Upskilling Programs

1. Professional Program in Data Science with Machine Learning Essentials from NIIT

Professional Program in Data Science with Machine Learning Essentials from NIIT is a 15-30 week online course that covers the fundamentals and applications of data analytics and machine learning.

Course content & Highlights:

• Data Analytics Using Excel
• Analytics using SQL
• Introduction to Programming using Python
• Python for Data Science
• Exploratory Data Analysis
• Exploratory Data Analysis using Tableau
• Storytelling using Tableau
• Statistics using Python
• Predictive Modelling using Machine Learning
• Capstone project
• Online self-paced study
• Weekly live sessions
• Course materials, videos, quizzes, assignments
• Webinars
• Improve problem-solving, creativity, and critical thinking
• Certificate from NIIT and StackRoute

2. Machine Learning Program from NIIT

The Machine Learning Program from NIIT is a comprehensive 40-week course that covers the entire spectrum of machine learning, from data analytics and visualization to predictive modeling and forecasting.

Course Content and Highlights:

• Data Analytics Using Excel
• Analytics using SQL
• Introduction to Programming using Python
• Python for Data Science
• Exploratory Data Analysis
• Exploratory Data Analysis using Tableau
• Storytelling using Tableau
• Capstone project 1
• Statistics & Data Visualization using Python
• Data Modelling using Machine Learning – part 1
• Data Modelling using Machine Learning – part 2
• ML Mini Project
• Time Series Forecasting
• Capstone Project 2
• Online and self-paced study with weekly live sessions and mentor support
• Course materials, videos, quizzes, assignments, and projects on the online learning platform
• Industry Projects
• Mentorship and Guidance from Experts
• Certification and Accreditation from NIIT and StackRoute
• Job Assistance and Placement Support

3. Post Graduate Program in AI and Machine Learning from Simplilearn

Simplilearn's Post Graduate Programme in AI and Machine Learning teaches data science, machine learning, and the newest AI principles and applications.

Course Content and Highlights:

• Programming using Python and R
• Statistics and Data Wrangling
• Data Visualization and Exploratory Data Analysis
• Machine Learning Algorithms and Techniques
• Deep Learning using TensorFlow and Keras
• Natural Language Processing and Computer Vision
• Artificial Intelligence and Big Data
• Cloud Computing using AWS and Azure
• Spark and Hadoop

Conclusion

The journey to learning machine learning begins with a solid foundation in programming and mathematics, progresses through a variety of machine learning courses, and is enriched by big data analytics training. So, start learning to make a significant impact in the tech-driven landscape of tomorrow.

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