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Upgrade your skills with top notch courses from Sigillieum

TRAINING

We offer a variety of training courses on the latest and emerging technologies and offer internships and project opportunities for students. Sigillieum offers one of a kind training module tailor-made based on the students’ proficiency level in technology.

Placement

Our tie-up with leading MNC’s and our in-house team of experts ensure that our students get facilitated with the right opportunities.
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Why Sigillieum ?

Real-time Learning with Hands on Experience

Learn from the Experts

Great Lab Facilities

Course carved as per Industry Demands

Facilitating Job Opportunities

Opportunities to work with core Technical Experts

Personal Career Coach

Flexible Course Timings

Affordable Course Fees
&
Flexible Payment Options

What are you waiting for?

Join Now !

Need for Reskilling

It is hard to accept and acknowledge the hard fact that both technology & customer expectations of today will become redundant for tomorrow. It is a fast-paced world where in-demand skills of today become superfluous the very next moment. Upgrading one’s skills regularly is a must for an individual, be it a fresher or an experienced one, to stay in-demand. Nowadays, there is a shortage of talent and organizations are continuously on the lookout for people having desired skills.

Students these days need to develop and hone their skills to stay ahead of the competition and prepare themselves for their career. Sigillieum offers programs specifically designed for students – with a mix of both theory and practical knowledge to enhance their career opportunities.

Today’s world is a fast-paced one and the skill which is in-demand today can become a thing of the past tomorrow. An individual has to update his skills regularly to move ahead in his career. Sigillieum offers courses designed for working professionals with more emphasis on practice and application. The course is designed based on the feedback received from corporate professionals on current industry trends, needs and skills gap identified.

Sigillieum offers courses for corporates which are curated based on their requirements to mitigate the skills gap, improve the proficiency level of their employees and to upskill their employees. We offer training in niche categories like AI, ML, Data Science, etc.

Everyone in your batch is running a rat race to grab onto that dream job. Skills and projects are the two important prerequisites that play an upper hand in helping you to get hold of that golden opportunity. Real-world and potential employers expect exposure and real-time experience in their ideal candidates. Classrooms only teach and test the theoretical aspects of academics. But, it is up to the students themselves who have to carve out their career path by equipping themselves with relevant skills, extra exposure, and hands-on experience.

We at Sigillieum offer a platform for students to develop real-time projects and give them the hang of corporate exposure which cannot be found elsewhere. Interns get a chance to immerse themselves in real-time projects at Sigillieum and to work with some of the best experts in the industry.

Students face a tough situation when choosing their final year projects. They have to consider many things such as select an area of their interest, choose the right avenue for the project and seek expert guidance in completing the project. Colleges give high importance for these projects which gives them an idea on how successful the student was in applying theoretical knowledge into practice and any additional skill he/she may have acquired.

The project also helps the potential employers to test a candidate’s expertise in the projects and the knowledge they have acquired from it. At Sigillieum, we offer an avenue for students to implement a topic of their interest and provide them with a window of opportunity to gain knowledge by working on real-time industry projects.

Want to specialize in Artificial Intelligence (AI), Deep Learning (DL) and Machine Learning (ML)? Looking to make a career out of it?

Industries are often on the lookout for candidates who have put extra efforts in learning a particular skill they are interested in. More often than not, preference is given to those students who have taken pains and put efforts to learn and practice new things. We offer inplant training at Sigillieum which provides the students an option to choose the training modules of their interest and gain hands-on experience on industry relevant projects.

We have come up with a curated course that provides specific inplant training to students. This gives them an added advantage for working in skills they want to specialize in and get the required industry exposure. Both the real-time experience and exposure helps the students to leverage their aptitude in the highly competitive job market.
Sigillieum offers short term workshops in AI, ML, Data Science, and Machine Learning. Based on the needs of the individual and institution, courses will be curated and crafted.

Modes of Training

Students can opt for Classroom Training or Online Classes based on their needs.

Course Benefits

Blend learning with realtime projects
  • Industry Experts as Trainers
  • Curated based on Industry Demands
  • Placement Assistance
  • Work on mini projects
  • Certification

Courses Offered

Data science, Machine Learning and Artificial Intelligence with Python

This course gives the student a complete picture of Data science, Machine Learning, Artificial Intelligence and covers all the fundamentals of the technology using the popular programming language – Python.

It has two major components/objectives:
  • Understand the real-life usage of ML,AI and Data Science
  • End to End understanding & application of all the concepts

Who should attend this course?

Anyone who is interested in making a career out of ML technology from students to working professionals and someone looking for a career change can opt for this course. Those from the IT, Engineering and Mathematics background will have an added advantage.

Course Benefits

Designed As Per Industry Standards

Expert Teachers & Instructors

Timely Doubt Resolution

Dedicated Assigned Mentors

Live Projects

Case Study Based Learning

24/7 Support

Work with our inhouse team on the current live projects and get an opportunity to implement your practical knowledge.

Classroom Training: NA

Online Training: Weekdays / Weekends

Start Date: Beginning of every month

Batches: Weekdays / Weekends

Contact us for in person training
hello@sigiliieum.com.
+91-88259 35922.

Fill in the details and one of our team members will reach out to you soon.

Data Science, Machine Learning, Artificial Intelligence with Python

Actual Fee: ₹40,000.00
Discounted Fee: ₹20,000.00 (50% Discount)
Duration: 60 hours
Module 1
  • Introduction to Python
  • Introduction to Data Science
  • Introduction to Machine Learning
  • Introduction to Artificial Intelligence
  • Data Science in Industries
Module 2
  • Introduction
  • Environment Setup
  • Math Operations / Precedence
  • Variable Assignment
  • Print / Get User Input
Module 3
  • Strings
  • Lists
  • Dictionaries / Booleans
  • Tuples / Sets
Module 4
  • Comparison Operators
  • Logical Operators
  • Conditional Statements
  • Loops
  • For Loop
  • Enumerate
  • Range
  • Break and Continue
  • Nested
Module 5
  • List Comprehension
  • Functions
  • Lambda
  • Map
  • Filter
Module 6
  • Numpy
  • Pandas
  • Matplotlib
Module 7
  • Python Based Website
  • Python Based Game
  • Assignments
Module 8
  • Machine Learning
  • Supervised, Unsupervised and Reinforcement Learning
  • Linear Regression
  • Sum of Squares
  • Data Importing
  • Data Visualisation
  • Model Training
  • Model Testing and Evaluation
Module 9
  • Applications
  • Learning Vocabulary
  • ANN Basics
  • CNN Overview
Module 10
  • Convolution Operation
  • Rectified Linear Units
  • Max Pooling and Down Sampling
  • Regularisation and Dropouts
  • Applications
Talk to advisor

Data Science Using Python -Master Course

Sigillieum offers one of the best courses on Data Science which covers all the related concepts in-depth. You will get to learn all the concepts from experienced working professionals and helps to deepen your knowledge of Data Science, Machine Learning & Deep Learning. By taking this course, you can benefit from the following ways:

  • Learn to get started with Data Science
  • A deeper knowledge of ML concepts, Deep Learning and Neural Networks
  • Train using case studies & live projects

Who should attend this course?

Anyone who is interested in making a career out of ML technology from students to working professionals and someone looking for a career change can opt for this course. Those from the IT, Engineering and Mathematics background will have an added advantage.

Course Benefits

Designed As Per Industry Standards

Timely Doubt Resolution

Dedicated Assigned Mentors

Expert Teachers & Instructors

Case Study Based Learning

Live Projects

24/7 Support

Work with our inhouse team on the current live projects and get an opportunity to implement your practical knowledge.

Classroom Training: NA

Online Training: Weekdays / Weekends

Start Date: Beginning of every month

Batches: Weekdays / Weekends

Contact us for in person training
hello@sigiliieum.com.
+91-88259 35922.

Fill in the details and one of our team members will reach out to you soon.

Data Science With Python – Master Course

Actual Fee: ₹1,00,000.00
Discounted Fee: ₹50,000.00 (50% Discount)
Duration: 75 hours
Introduction to Artificial Intelligence
  • Applications, Industries and Growth
  • Techniques used in AI
  • AI for Everything
  • Different methods used in AI
  • Tradition Methods & New Methods
  • AI Agents
Python: Environment Setup and Essentials
  • Introduction to Anaconda
  • Installation of Anaconda Python Distribution: For Windows, Mac OS and Linux
  • Jupyter Notebook Installation
  • Jupyter Notebook Introduction
  • Variable Assignment
  • Basic Data Types: Integer, Float, String, None and Boolean; Typecasting
  • Creating, accessing and slicing tuples
  • Creating, accessing and slicing lists
  • Creating, Viewing, accessing and modifying dicts
  • Creating and using operations on sets
  • Basic Operators: ‘in’, ‘+’, ‘*’
  • Functions
  • Control Flow
  • Mathematics Computing with Python (Numpy)
Statistics and Probability
  • Descriptive Statistics & Data distribution
  • Probability Concepts and Set theory
  • Probability Mass Functions
  • Probability Distribution Functions
  • Cumulative Distribution Functions
  • Modeling Distributions
  • Inferential Statistics
  • Estimation
  • Hypothesis Testing
  • Implementation of Statistics Concepts in Python
Linear Algebra
Machine Learning Models in Python
  • Building models using below algorithms
  • Linear and Logistics regression
  • Decision Trees
  • Support Vector Machines (SVM)
  • Random Forests
  • XGBoost
  • K Nearest Neighbour & Hierarchical Clustering
  • Principal Component Analysis
  • Text Analytics and Time Series Forecasting
Data Visualization using Matplotlib and Tableau
  • Interactive Visualizations with Matplotlib
  • Data Visualizations using Tableau
  • Tableau Dashboard and Story Board
  • Tableau and R integration
Numpy Overview
  • Properties, Purpose and Types of ndarray
  • Class and Attributes of ndarray object
  • Basic Operations: Concept and Examples
  • Accessing Array Elements: Indexing, Slicing, Iteration, Indexing with Boolean Arrays
  • Copy and Views
  • Universal Functions (ufunc)
  • Shape Manipulation
  • Broadcasting
  • Linear Algebra
Data Manipulation with Python (Pandas)
  • Introduction to Pandas
  • Data Structures
  • Series
  • DataFrame
  • Missing Values
  • Data Operations
  • Data Standardization
  • Pandas File Read and Write Support
  • Data Acquisition (Import & Export)
  • Selection, Filtering, Combining and Merging Data Frames, Normalization method
  • Removing Duplicates & String Manipulation
Data Visualization in Python using Matplotlib
  • Introduction to Data Visualization
  • Python Libraries
  • Plots
  • Matplotlib Features
  • Line Properties Plot with (x, y)
  • Controlling Line Patterns and Colors
  • Set Axis, Labels, and Legend Properties
  • Alpha and Annotation
  • Multiple Plots
Linear Regression
  • Regression Problem Analysis
  • Mathematical Modeling of Regression Model
  • Gradient Descent Algorithm
  • Building simple Univariate Linear Regression Model
  • Multivariate Regression Model
  • Best Fit Line and Linear Regression
Logistic Regression
  • Problem Analysis
  • Cost Function Formation
  • Mathematical Modelling
  • Digit Recognition using Logistic Regression
Deep Learning using Tensorflow
  • Basics of Neural Network
  • Linear Algebra
  • Implementation of Neural Network in Vanilla
  • Basics of TensorFlow
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Generative Models
  • Semi-Supervised Learning using GAN
  • Seq-to-Seq model
  • Encoder and Decoder
Artificial Neural Networks
  • Neurons, ANN & Working
  • Single Layer Perceptron Model
  • Multilayer Neural Network
  • Feed Forward Neural Network
  • Cost Function Formation
  • Applying Gradient Descent Algorithm
  • Backpropagation Algorithm & Mathematical Modelling
  • Programming Flow for backpropagation algorithm
  • Programming SLNN using Python
  • Programming MLNN using Python
  • Digit Recognition using MLNN
  • XOR Logic using MLNN & Back propagation
Clustering
  • Hierarchical Clustering
  • K Means Clustering
  • Use Cases for K Means Clustering
  • Programming for K Means using Python
  • Image Color Quantization using K Means Clustering Technique
Principle Component Analysis
  • Dimensionality Reduction, Data Compression
  • Concept and Mathematical modeling
Deep Dive into Neural Networks
  • Understand limitations of A Single Perceptron
  • Understand Neural Networks in Detail
  • Backpropagation : Learning Algorithm
  • Understand Backpropagation : Using Neural Network Example
Master Deep Networks
  • SONAR Dataset Classification
  • Feature Extraction
  • Working of a Deep Network
  • Training using Backpropagation
  • Variants of Gradient Descent
  • Types of Deep Networks
Convolutional Neural Networks (CNNs)
  • Introduction to CNNs
  • CNNs Application
  • Architecture of a CNN
  • Convolution and Pooling layers in a CNN
  • Understanding and Visualizing a CNN
  • Transfer Learning and Fine-tuning Convolutional Neural Networks
  • Image classification using Keras deep learning library
Recurrent Neural Networks (RNNs)
  • Intro to RNN Model
  • Application use cases of RNN
  • Modelling sequences
  • Training RNNs with Backpropagation
  • Long Short-Term memory (LSTM)
  • Recursive Neural Tensor Network Theory
  • Recurrent Neural Network Model
  • NLP Example using Keras library
  • Time-Series Analysis
Python Libraries
  • Numpy
  • Matplotlib
  • Pandas
  • Theano
  • Scikit-learn
  • Opencv
  • TensorFlow
  • Keras
Talk to advisor

Python for Machine Learning

Sigillieum offers one of the best courses on Python which covers all the related concepts in-depth. You will get to learn all the concepts from experienced working professionals and helps to deepen your knowledge of Machine Learning & Deep Learning.

Who should attend this course?

Anyone who is interested in making a career out of ML technology from students to working professionals and someone looking for a career change can opt for this course. Those from the IT, Engineering and Mathematics background will have an added advantage.

Course Benefits

Designed As Per Industry Standards

Timely Doubt Resolution

Dedicated Assigned Mentors

Expert Teachers & Instructors

Case Study Based Learning

Live Projects

24/7 Support

Work with our inhouse team on the current live projects and get an opportunity to implement your practical knowledge.

Classroom Training: NA

Online Training: Weekdays / Weekends

Start Date: Beginning of every month

Batches: Weekdays / Weekends

Contact us for in person training
hello@sigiliieum.com.
+91-88259 35922.

Fill in the details and one of our team members will reach out to you soon.

Python for Machine learning

Actual Fee: ₹20,000.00
Discounted Fee: ₹10,000.00 (50% Discount)
Duration: 25 hours
Short Introduction
  • What is Script, program?
  • Types of Scripts
  • Difference between Script and Programming Languages
  • Features and Limitation of Scripting
  • Types of programming Language Paradigms
  • Introduction to Python
Introduction to Python
  • What is Python?
  • Why Python?
  • Who Uses Python?
  • Characteristics of Python
  • History of Python
  • What is PSF?
  • Python Versions
  • How to Download and Install Python
  • Install Python with Diff IDEs
  • Features and Limitations of Python
  • Python Applications
  • Creating Your First Python Program
  • Printing to the Screen
  • Reading Keyboard Input
  • Using Command Prompt and GUI or IDE
  • Python Distributions
Different Modes in Python
  • Execute the Script
  • Interactive and Script Mode
  • Python File Extensions
  • SETTING PATH IN Windows
  • Clear screen inside python
  • Learn Python Main Function
  • Python Comments
  • Quit the Python Shell
  • Shell as a Simple Calculator
  • Order of operations
  • Multiline Statements
  • Quotations in Python
  • Python Path Testing
  • Joining two lines
  • Python Implementation Alternatives
  • Sub Packages in Python
  • Uses of Python in Data Science, IoT
  • Working with Python in Unix/Linux/Windows/Mac/Android..!!
Python New IDEs
  • PyCharm IDE
  • How to Work on PyCharm
  • PyCharm Components
  • Debugging process in PyCharm
  • PYTHON Install Anaconda
  • What is Anaconda?
  • Coding Environments
  • Spyder Components
  • General Spyder Features
  • Spyder Shortcut Keys
  • Jupyter Notebook
  • What is Conda? and Conda List?
  • Jupyter and Kernels
  • What is PIP?
Variables in Python
  • What is Variable?
  • Variables and Constants in Python
  • Variable,Variable names and Value
  • Mnemonic Variable Names
  • Values and Types
  • What Does “Type” Mean?
  • Multiple Assignment
  • Python different numerical types
  • Standard Data Types
  • Operators and Operands
  • Order of Operations
  • Swap variables
  • Python Mathematics
  • Type Conversion
  • Mutable Versus Immutable Objects
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
  • Membership Operators
  • Identity Operators
  • Operator precedence
  • Evaluating Expressions
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”
  • if .. elif .. else statement (Multi-way)
  • When “else condition” does not work
  • How to use “elif” condition
  • How to execute conditional statement with minimal code
  • 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 statement, 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
  • Accessing Values in Strings
  • Various String Operators
  • Some more examples
  • Python String replace() Method
  • Changing upper and lower case strings
  • Using “join” function for the string
  • Reversing String
  • Split Strings
Sequence or Collections in Python
  • Strings
  • Unicode Strings
  • Lists
  • Tuples
  • buffers
  • xrange
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
  • Tuple Membership Test
  • Built-in functions with Tuple
  • Dotted Charts
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
Python Dictionary
  • How to create a dictionary?
  • PYTHON HASHING?
  • Python Dictionary Methods
  • Copying dictionary
  • Updating Dictionary
  • Delete Keys from the dictionary
  • Dictionary items() Method
  • Sorting the Dictionary
  • Python Dictionary in-built Functions
  • 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
  • Significance of Indentation (Space) in Python
  • How Function Return Value?
  • Types of Arguments in Functions
  • Default Arguments and Non-Default Arguments
  • Keyword Argument and Non-keyword Arguments
  • Arbitrary Arguments
  • Rules to define a function in Python
  • Various Forms of Function Arguments
  • Scope and Lifetime of variables
  • Nested Functions
  • Call By Value, Call by Reference
  • Anonymous Functions/Lambda functions
  • Passing functions to function
  • map(), filter(), reduce() functions
  • What is a Docstring?
Advanced Python
Python Modules
  • What is a Module?
  • Types of Modules
  • The import Statement
  • The from…import Statement
  • ..import * Statement
  • Underscores in Python
  • The dir( ) Function
  • Creating User defined Modules
  • Command line Arguments
  • Python Module Search Path
Packages in Python
  • What is a Package?
  • Introduction to Packages?
  • py file
  • Importing module from a package
  • Creating a Package
  • Creating Sub Package
  • Importing from Sub-Packages
  • Popular Python Packages
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 File 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 OS Module
  • Shell Script Commands
  • Various OS operations in Python
  • Python File System Shell Methods
Python Exception Handling
  • Python Errors
  • Common RunTime Errors in PYTHON
  • Abnormal termination
  • Chain of importance Of Exception
  • Exception Handling
  • Try … Except
  • Try .. Except .. else
  • Try … finally
  • Argument of an Exception
  • Python Custom Exceptions
  • Ignore Errors
  • Assertions
  • UsingAssertionsEffectively
More Advanced Python
  • Python Iterators, Generators, Closures, Decorators
Talk to advisor

Corporate Training

The ever widening skills gap has become a challenge for organizations as it comes in their ability to compete in the highly competitive market. Companies are leveraging the services of corporate trainers to overcome the skills gap and to expand the skillsets of their internal resources. Sigillieum offers corporate training services in Chennai for a variety of courses related to latest and emerging technologies. We have designed our courses to meet the demands and industry standards of the corporate world. Our faculties are comprised of industry experts with a wealth of experience and are adept at providing live lectures to the intended group.

Benefits

Instructor Led Live Group

Customized Courses

Hands On Learning

Industry Standard Materials

Training Intended To Achieve Business Goals

Contact Us

Testimonials

Vishal Sreenivasan

A great place to learn computer vision. Industrial level projects are deployed on regular basis and the co workers are kind for the requests.

Sathish Kumar

Very worthwhile course, full of practical learning, delivered by a very knowledgeable and engaging tutor.

Ramanad Sagar

very informative course and the trainer was extremely helpful.

Shruthi

It was excellent. The trainer was very knowledgeable and the staff was very friendly. Everyone was very helpful. I will recommend sigillieum to my friends. Also, I will surely take more classes.

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Sigillieum Limited

Unit 7b Cranbrook House 61 Cranbrook Road
Ilford London IG1 4PG
United Kingdom

hello@sigillieum.com
+44 20 3239 0

INDIA OFFICE

Sigillieum Software Consultants Pvt. Ltd
No: #15, 62nd Street, Ashok Nagar Chennai, Tamil Nadu – 600083
hello@sigillieum.com
+91 88259 35922
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