Certification Program in
ML & DL
using Python
Course Duration
- 90 Hours
- 5 sessions/week
Tools Covered
- Python
- Machine Learning
- Deep Learning
Learning Mode
- Online Live Classes
- One on one Interactive session
We provide
- Special sessions for doubt solving
- Sessions recordings (on request)
- Sessions documents (on request)
- Assignments Mock interview
- Live Projects
Python Full Course Content
Introduction to Python
- What is Python?
- Why Python?
Variables in Python
- What is Variable?
- Variables and Constants in Python
- Variable, names and Value
- Values and Types
- What Does “Type” Mean?
String Handling
- What is string?
- String operations and indices
- Basic String Operations
- String Functions, Methods
- Delete a string
- String Multiplication and concatenation
- Python Keywords, Identifiers and Literals
- String Formatting Operator
- Structuring with indentation in Python
- Built-in String Methods
- Define Data Structure?
- Data Structures in PYTHON
Python Operators and Operands
- Arithmetic, Relational Operators and Comparison Operators
- Python Assignment Operators
- Short-hand Assignment Operators
- Logical Operators or Bitwise Operators
Python Conditional Statements
- How to use “if condition” in conditional structures
- if statement (One-Way Decisions)
- if .. else statement (Two-way Decisions)
- How to use “else condition”
- Logical Operators or Bitwise Operators
- if .. elif .. else statement (Multi-way)
- How to use “elif” condition
Nested IF Statement
Python LOOPS
- How to use “While Loop” and “For Loop”
- How to use For Loop for set of other things besides numbers
- Break statements, Continue statements, Enumerate
- function for For Loop
- Practical Example
- How to use for loop to repeat the same statement over and again
- Break, continue statements
Learning Python Strings
- Strings
- Lists
- Tuples
Python Lists
- Lists are mutable
- Getting to Lists
- List indices
- Traversing a list
- List operations, slices and methods
- Map, filter and reduce
- Deleting elements
- Lists and strings
Python TUPLE
- Advantages of Tuple over List
- Packing and Unpacking
- Comparing tuples
- Creating nested tuple
- Using tuples as keys in dictionaries
- Deleting Tuples
- Slicing of Tuple
Python Sets
- How to create a set?
- Iteration Over Sets
- Python Set Methods
- Python Set Operations
- Union of sets
- Built-in Functions with Set
- Python Frozenset
Variables in Python
- What is Variable?
- Variables and Constants in Python
- Variable, names and Value
- Values and Types
- What Does “Type” Mean?
Python Dictionary
- How to create a dictionary?
- Python Dictionary Methods
- Copying dictionary
- Updating Dictionary
- Delete Keys from the dictionary
- Dictionary items() Method
- Sorting the Dictionary
- Python Dictionary in-built Function
- Dictionary len() Method
- Variable Types
- Python List cmp() Method
- Dictionary Str(dict)
Python Functions
- What is a function?
- How to define and call a function in Python
- Types of Functions
- How Function Return Value?
- Types of Arguments in Functions
- Default Arguments and Non-Default
Arguments - Keyword Argument and Non-keyword
Arguments - Rules to define a function in Python
- Scope and Lifetime of variables
- Nested Functions
- Call By Value, Call by Reference
- Passing functions to function
Python Date and Time
- How to Use Date & DateTime Class
- How to Format Time Output
- How to use Timedelta Objects
- Calendar in Python
- datetime classes in Python
- How to Format Time Output?
- The Time Module
- Python Calendar Module
- Python Text Calendar, HTML Calendar Class
- Unix Date and Time Commands
File Handling
- What is a data, Information File?
- File Objects
- File Different Modes and Object Attributes
- How to create a Text Fil and Append Data to a File and Read a File
- Closing a file
- Read, read line ,read lines, write, write
lines…!! - Renaming and Deleting Files
- Directories in Python
- Working with CSV files and CSV Module
- Handling IO Exceptions
Python Exception Handling
- Chain of importance Of Exception
- Exception Handling
- Try … Except
- Try .. Except .. else
- Try … finally
- Argument of an Exception
- Python Custom Exceptions
- Ignore Errors
- Assertions
- Using Assertions Effectively
More Advanced PYTHON
- Python Iterators, Generators, Closures,
Decorators and Python @property
Python Class and Objects
- Introduction to OOPs Programming
- Object Oriented Programming System
- OOPS Principles
- Define Classes
- Creating Objects
- Class variables and Instance Variables
Constructors - Basic concept of Object and Classes
Machine Learning Full Course Syllabus
1. Introduction to Machine Learning
- Machine Learning
- Machine Learning Algorithms
- Algorithmic models of Learning
- Applications of Machine Learning
- Large Scale Machine Learning
2. Techniques of Machine Learning
- Supervised Learning
- Unsupervised Learning
3. Regression
- Regression and its Types
- Logistic Regression
- Linear Regression
- Polynomial Regression
4. Classification
- Meaning and Types of Classification
- Nearest Neighbor Classifiers
- K-nearest Neighbors
- Probability and Bayes Theorem
- Support Vector Machines
- Naive Bayes
- Decision Tree Classifier
- Random Forest Classifier
5. Unsupervised Learning: Clustering
- About Clustering
- Clustering Algorithms
- K-means Clustering
- Hierarchical Clustering
- Distribution Clustering
6. Model optimization and Boosting
- Ensemble approach
- K-fold cross validation
- Grid search cross validation
- Ada boost and XG Boost
Deep Learning Full Course Syllabus
1. Introduction to Deep Learning
- • What are the Limitations of Machine Learning?
- What is Deep Learning?
- Advantage of Deep Learning over Machine
learning - Reasons to go for Deep Learning
- Real-Life use cases of Deep Learning
2. Deep Learning Networks
- What is Deep Learning Networks?
- Why Deep Learning Networks?
- How Deep Learning Works?
- Feature Extraction
- Working of Deep Network
- Training using Back propagation
- Types of Deep Networks
- Feed forward neural networks (FNN)
- Convolutional neural networks (CNN)
- Recurrent Neural networks (RNN)
3. Deep Learning with Keras
- Define Keras
- How to compose Models in Keras?
- Predefined Neural Network Layers
- What is Batch Normalization?
- Saving and Loading a model with Keras
- Customizing the Training Process
- Intuitively building networks with Keras
4. Convolutional Neural Networks (CNN)
- Introduction to Convolutional Neural
Networks - CNN Applications
- Architecture of a Convolutional Neural
Network - Convolution and Pooling layers in a CNN
- Understanding and Visualizing CNN
- Transfer Learning and Fine-tuning
Convolutional Neural Networks
5. Recurrent Neural Network (RNN)
- Intro to RNN Model
- Application use cases of RNN
- Modelling sequences
- Training RNNs with Back propagation
- Long Short-Term Memory (LSTM)
- Recursive Neural Tensor Network Theory
- Recurrent Neural Network Model
- Time Series Forecasting