Master in Artificial Intelligence And Machine Learning Course

Name: Best Machine Learning Course | Online/Offline Class | SMEClabs
Price: 70000 INR
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Join the webinar on Master in Artificial Intelligence And Machine Learning Course

05-Apr-2025 Register Now

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Years of R & D in Syllabus

Machine Learning

This online course offers an in-depth overview of machine learning topics, including working withreal-time data, developing algorithms using supervised and unsupervised learning, regression, classification, and time series modeling. You will also learn how to use Python to draw predictions from data.

Program Features:

Online/offline learning
Instructor-led training
Interactive learning with Jupyter notebooks and pycharm integrated labs
Dedicated mentoring session from faculty of industry experts

Master in Artificial Intelligence And Machine Learning Course - Syllabus

Python

Data Types
Variables
Operators
Control Statements and Loops
List
Tuples
Dictionaries
Sets
Functions, Lambda Functions
Modules, Built-In Modules, Packages
Exceptions
File Handling and Regular expressions
Object-Oriented Approach: Classes, Methods, Objects.

MySQL

Installation, Database creation
Insert Query
Select Query
WHERE Clause
Update Query
DELETE Query
LIKE Clause
Sorting Results
Joins
Constraints
ALTER Command
Aggregate functions

MongoDB

CRUD Operations,
Insert Many
Update and Update Many
Delete and Delete Many,
Introduction to Embed Documents,
Embed Documents in Action
Adding Arrays
Fetching Data from Structured Data

Matplotlib

Line plot
Scatter plot
Bar charts
Histogram,
Pie Carts
Stack charts
Legend title Style
Figures and subplots
Plotting function in pandas
Labelling and arranging figures
Save plots

Seaborn

Style functions
Color palettes
Box Plot
Count Plot
KDE Plot
Pair Plot
Distribution plots
Categorical plots
Regression plots
Axis grid objects.

NumPy

Creating NumPy arrays
Indexing and slicing in NumPy
Downloading and parsing
Creating multidimensional arrays
NumPy Data types,
Array attributes
Indexing and Slicing,
Creating array views copies
Manipulating array shapes I/O.

Pandas

Series and Data Frames
Grouping,
Aggregating
Merge Data Frames
Generate summary tables
Group data into logical pieces
Manipulate dates
Creating metrics
Data wrangling
Merging and joining

Scikit-learn

Feature extraction
Pre-processing
Splitting data for training and testing
Regression
Classification
Model evaluation metrics and model,
Hyper parameter tuning
model optimization
Saving and opening a model

Keras

Introduction to Deep Learning
Image augmentation
Biological Neural Networks
Artificial Neural Network
Introduction to Deep Learning Libraries
Regression Models
Classification Models
Deep Neural Networks architecture and implementations
Artificial Neural Network
Convolutional Neural Networks
Recurrent Neural Networks
Activation Function
Hyper parameter Tuning
Model Optimizations.

TensorFlow & PyTorch

Introduction to frameworks
Regression and Classification.
CNN History and evolution
Feature extraction
Pre-processing
Image augmentation
Artificial Neural Network
Convolutional Neural Networks
Recurrent Neural Networks
CNN Application
Distributed Computing
Exporting and importing models
Multi-Layer Perceptron Learning,
Hidden Layers architecture of Perceptron
Optimizers
Gradient Descent Optimization, Forming Graphs
Image Recognition
Pretrained Models

Natural Language Tool Kit(NLTK)

Introduction to NLP
Linguistic Resources
Word Level Analysis,
Syntactic Analysis
Semantic Analysis
Word Sense Disambiguation,
Natural Language Discourse Processing
Part of Speech (PoS) Tagging
Natural Language Processing – Inception
NLP – Information Retrieval
Applications of NLP
Natural Language Processing – Python (NLTK)

Hugging Face and Yolo

Explore pre-trained models and datasets
Understanding transformers library for NLP
Diffusers for generative models.
A real-time object detection algorithm with yolo known for its speed and accuracy.
Class and bounding box coordinates

LangChain and Llama

Process of building applications utilize large language models (LLMs) like GPT,,LLaMA.
Text generation
Summarization
Question answering.
Designed to be fine-tuned and adapted for specific use cases or domains.
Building applications that require multiple LLM calls and interactions with external systems

ChatGPT and Gemini

Integrate cutting-edge advancements in AI with a focus on deeper understanding and reasoning
Solve sophisticated tasks in software development, such as architectural planning, advanced problem-solving, and intricate algorithm design.
Offers interactive, human-like conversations and can be fine-tuned for specific domains or tasks.
Structured, logical approach to software engineering, often excelling in tasks that demand higher precision and domain-specific knowledge

** The above is the lite syllabus and doesn’t cover the full syllabus. To get full syllabus Book a Free Demo Now