Machine Learning (ML) is a branch of artificial intelligence (AI) that enables systems to learn from data and improve their performance on specific tasks without being explicitly programmed. It involves creating algorithms that can identify patterns, make decisions, or predict outcomes based on input data.
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Career Growth Prospects
The career growth prospects in Machine Learning (ML) are exceptionally promising, driven by the increasing reliance on artificial intelligence (AI) and automation across industries. Here’s an overview of the opportunities and potential career trajectory in machine learning:
High Demand and Growth
Machine learning professionals are in high demand across diverse sectors such as technology, healthcare, finance, retail, and manufacturing.
Career Path and Roles
Machine learning offers a wide range of career roles, each with a clear progression path with entry-Level roles (0–2 years) like ML Engineer, Data Scientist, AI Engineer, Junior Data Analyst or mid-Level roles (3–6 years) like Senior ML Engineer etc.
Competitive Salaries
Machine learning professionals command some of the highest salaries in the tech industry due to their specialized skills, Entry-level roles often offer lucrative packages, and salaries increase significantly with experience and expertise.
Opportunities for Specialization
Professionals can specialize in areas like: Natural Language Processing (NLP), Computer Vision, Reinforcement Learning, Big Data & Scaleable ML, Edge AI.
Key Takeaways
Industry recognized Certificate
Industry led Content
Lifetime access to LMS
Notes, Codes & Lectures
Value addition in Resume
Learn from Industry Leaders
Doubt Clearing Support
Course Curriculum
Introduction
Overview of Machine Learning,
Starting with Machine Learning,
Overview of this training,
Terminologies in Machine Learning
Machine Learning
Introduction to Machine Learning,
What is Machine Learning?,
Types of Machine Learning,
How Machine Learning works?
Usage of Machine Learning.
Revisiting Python
Introduction to Python Programming,
Introduction to Python and Anaconda,
Working on Jupyter IDE,
Conditional statements in Python,
Different types of data,
List,Tuple Dictionary,
Loops
Function & Packages
Function,
Packages,
Installing different packages of Python
Python Libraries
Working on Various Python Libraries,
NumPy,
Pandas,
Matplotlib,
Scikit-learn
NumPy
Working on NumPy,
Introduction to Numpy Array,
Creating arrays of different Dimensions,
Indexing,
Data processing using Array
Pandas
Data Analysis using Pandas,
Introduction to Pandas,
Data Type of Pandas,
Creating Dataframe using Pandas,
Importing Dataset using Pandas,
Various operations on data using Pandas tools
Matplotlib
Data visualization using Matplotlib,
Plotting data using Matplotlib library,
Using various tools of Matplotlib,
Types of Graph,
Implementation of different types of Graphs
Scikit-Learn
Applying Algorithms on Dataset using Scikit-learn,
Data splitting,
Using different algorithms for dataset,
Prediction,
Score check
Machine Learning Algorithms
Regression analysis
Simple linear regression
Multi linear regression
Classification
Binary class classification
Multi class classification
Support Vector Machine
KNN algorithm
High Demand and Growth
Career Path and Roles
Competitive Salaries
Opportunities for Specialization
Courses