Python for Machine Learning

Overview

Our Python for Machine Learning Training program focuses on mastering the application of Python in implementing machine learning algorithms. It encompasses essential topics including data manipulation, data analysis, visualization, and a comprehensive grasp of diverse machine learning algorithms - their mechanics and implementation using Python. This training holds significant value across industries, as Python's versatility and user-friendliness make it the perfect fit for constructing scalable machine learning models

Prerequisites

There are no specific prerequisites for Python Training A basic understanding of Computer Programming terminologies is beneficial if you’re a beginner.

Curriculum

Introduction to Python and Basics

• History
• Features
• Definition & Applications
• Features, Versions & Working
• Anaconda & Different IDEs for Python
• Introduction to IDE's - Jupyter Notebook, Spyder & Google Colab

Data Types and Control Flows

• Literals, reserved words and input functions
• Data Types: int, float, bool, str
• Decision Control Flows: If / Nested If / If-else / If-elif-else
• Control Flow Loops: While loop, For loop, While-else, For-else
• Operators: Arithmetic, Relational or Comparison, Logical

Lists, Tuples, Sets, and Dictionaries

• Operators (Bitwise, Assignment, Ternary)
• List: Traversing Elements, Operations, Methods, Membership Operator, Comprehension, Ways of Accessing values.
• Tuples: Creating Tuples, Ways of Accessing Values, Tuple Vs Immutability, Tuple Comprehension
• Sets: Ways of Accessing Values, Manipulating and Accessing Sets, Set Operations, Creating Sets
• Dictionary: Why Dictionary, creating a Dictionary, Accessing Values, Updating Dictionaries, Functions of Dictionary

File Handling and Strings

• File Handling: Types of Files, Opening and Closing Files, Writing, Appending, and Reading Files
• Strings: String Literals, Single, Double & Triple Quotes, Raw Strings and Operations on strings
• Dictionary: Accessing Values, Updating Dictionaries, Functions of Dictionary

Iterators & Generators

• Iterator vs Iterable, Containers, Generators in Python.

Regular Expressions

• Match function
• Search function
• Matching VS Searching
• Modifiers
• Patterns
• Uses of Regular Expressions - Text Analytics, import re, Character Classes, Backslash, Alteration, Quantifiers

OOPs concept

• Class and object
• Attributes
• Inheritance
• Overloading
• Overriding
• Data hiding

Introduction to NumPy, Pandas & Matplotlib

• Introduction to NumPy, Install NumPy
• Array Creation, Array Reshaping, Indexing, Operations
• Introduction to Pandas, Slicing Data, Slicing Data Frame

Introduction to Data Preprocessing

• Filtering DataFrame, Transforming DataFrame, Advanced Indexing

Exploratory Data Analysis (EDA)

• Data Cleaning Techniques, Handling Missing Data, Handling Categorical Data
• Introduction to EDA, 2D Scatter-plot, 3D Scatter-plot, Pair plots
• Univariate, Bivariate, and Multivariate Analysis, Box-plot
• Variance and Standard Deviation, Median, IQR (Interquartile Range)

Advanced Pandas and Data Visualization

• Advanced Pandas, Advanced Indexing, Data Preparation
• Handling Missing Data, handling Categorical Data, Data Cleaning

Data Visualization

• Introduction to Data Visualization, Plotting with Matplotlib
• Scatter Plots, Line Plots, Bar Plots, Pie Charts, Heatmaps

Features

• Personalised Learning Plan
• Flexible Scheduling
• Expert Instructor
• Hands-on Project-Based Training
• Support After Training
• Interview Preparation

Course Fees

Virtual Instructor-Led Training

One-to-One Private Batch	Public Batch
Fees : ₹80,000 + 18% GST	Fees : ₹15,000 + 18% GST
2hrs : Mon - Fri	2hrs : Mon - Fri
4hrs : Sat - Sun	4hrs : Sat - Sun