What this Course Includes?
- Technology Training
- Aptitude Training
- Learn to Code (Codeathon)
- Real Time Projects
- Learn to Crack Interviews
- Panel Mock Interview
- Unlimited Interviews
- Life Long Placement Support
Monday (Monday - Friday)
Saturday (Saturday - Sunday)
Wednesday (Monday - Friday)
Friday (Monday - Friday)
Modes Of Training
Offline / Classroom Training
- A Personalized Learning Experience with Direct Trainer Engagement!
- Direct Interaction with the Trainer
- Clarify doubts then and there
- Airconditioned Premium Classrooms and Lab with all amenities
- Codeathon Practices
- Direct Aptitude Training
- Live Interview Skills Training
- Direct Panel Mock Interviews
- Campus Drives
- 100% Placement Support
Online Live Training
- Instructor Led Live Training! Learn at the comfort of your home
- No Recorded Sessions
- Live Virtual Interaction with the Trainer
- Clarify doubts then and there virtually
- Live Virtual Interview Skills Training
- Live Virtual Aptitude Training
- Online Panel Mock Interviews
- 100% Placement Support
- Blended Delivery model (both Online and Offline as per Clients’ requirement)
- Industry endorsed Skilled Faculties
- Flexible Pricing Options
- Customized Syllabus
- 12X6 Assistance and Support
The significance of learning AI is to make the computer systems learn on their own from data that are extracted from previous tasks and experiences. It is about learning how to pre-program computer devices with AI functionalities to perform a task. The learning of AI includes programming languages, advanced mathematics, statistics, linear algebra, calculus, machine learning, neural network technology, deep learning, and computer vision. Our Online AI Training equips the students with the ability to enable computers and machines to perform intellectual tasks such as decision-making, understanding of human communication, problem-solving, and perceptions
AI is booming technology in the world to build computational models of intelligence starts from robots that are playing chess and chatbots for responding customer questions to navigate real traffic intelligently for self-driving cars. Artificial Intelligence creates lucrative careers for learners around the globe with exponential job growth. This field remains competitive since it is introduced as it improves interests and innovative skills for today’s young minds. As well, the roles of this Artificial Intelligence field are a very niche that requires advanced knowledge and hands-on exposure. Launch your AI career or transform your career by joining our AI Online Training Institute. Following are the reasons to choose an Online AI Course for your bright future.
- AI is the in-demand skill of the century. It is creating 130 million roles in major global sectors.
- AI is everywhere and active 24/7 across the world through chatbots, self-driving cars, and security solutions.
- AI and ML algorithms are used to retrieve patterns for useful insights for businesses and customers around the world.
- AI gives bright careers for professionals and the average pay scale is around $100,000 per annum in the US and other international companies.
- AI is a versatile field and helps the learners stand out from the queue to perform important roles in banking, security, healthcare, fraud detection, mobile app development, and so on.
Learn the best AI Certification Course Online with 100% Placement Assistance at Softlogic for obtaining your desired jobs. Our Online AI Training Program is offered with instructor-led live sessions with complete hands-on practices by expert trainers. We equip you to become a master in AI skills to achieve your dream jobs in top MNC and IT companies. Book a free demo today to check out our Online AI Training Course.
The main goal of our Artificial Intelligence Online Training is to provide knowledge on intelligent systems and agents, reasoning with or without uncertainty, formalization of knowledge, machine learning applications, and basic level robot making. Our AI Online Course is specific, understandable, and clearly indicates the ability of students with performance tracker and industry-valuable certification. Following are the learning outcomes of our Online AI Training Course
- Fundamental understanding of AI with its foundations and history
- Implementation of basic principles of AI in solutions for problem-solving, perception, inference, learning, and knowledge representations.
- Fundamental understanding of AI techniques in applications like intelligent agents, artificial neural networks, machine learning models, and expert systems.
- Proficiency in application development with AI language, data mining tools, and expert system shell scripts.
- Well-versed in the implementation of scientific methods to models of machine learning.
- In-depth knowledge for sharing discussions of AI, scope, and limitations, and social implications
Our Online Artificial Intelligence Training with 100% Placement Assistance makes you an expert with industry-ready skills to work in various platforms like virtual assistants, chatbots, agriculture, farming, autonomous flying, retail, shopping, fashion, security, surveillance, sports, analytics, activities, manufacturing, production, livestock management, and inventory management.
- Industry-standard AI Coursework
- One-on-one or Small batch size
- Instructor-led live online mode
- Customizable course curriculum
- Industry-valued Certificate
- 4+ real-time project practices
- Instalment Options for fees
- Field Expertized Trainers
- Convenient learning hours
- Free soft skills training
- 100% Placement Assistance
- Free Lifetime Career Guidance
There is no prior expertise required for learning AI Course Online for freshers as we offer them the course from scratch. Our trainers will be allocated as per the convenient learning hours of students around the world and it can be regular classes or weekend classes or fast-track mode. We suggest working professionals have the following prerequisites to enjoy the complete hands-on experience on the new concepts.
- Strong knowledge of Mathematics
- Excellent Programming Knowledge
- Good Analytical Skills
- Understanding of complex algorithms
- Fundamental knowledge in statistics and modeling
Freshers and working professionals can learn AI Course Online at Softlogic as we are providing in-person classes along with other training modes for the students who want to study in our AI Training Institute in Chennai. It is beneficial for the students to launch their career in Information Technology, Economy, Business, and Other Industries. Following are the eligible category for learning Artificial Intelligence Online Training Course at Softlogic.
- Freshers with a degree in BBA, B.Sc/M.Sc Maths, MBA in Finance, Accounting, and Banking.
- Working professionals with experience in IT or non-IT fields like tech support, BPO, or process associate.
The field of Artificial Intelligence creates future-proof careers for the learners to obtain exciting jobs around the world and it opens the door of opportunities to work in personal assistants, healthcare, disease detection, disease prediction, surgery plans, defense, space science, business operations, industries like retail and robot manufacturing, heavy-lifting industries, security and surveillance, smart sales, and inventory management. Learn the best AI Online Training with 100% Placement Assistance at Softlogic to stay competitive for global jobs.
The learning of AI Online gives the students the career benefits such as increased efficiency, improved workflows, lower human errors, deeper data analysis, informed decision-making, organized information, personalized learning, immersive learning and growth, and community connections. Businesses around the world are adopting AI technologies as it saves time and money by automating and optimizing routine tasks for improved productivity and efficiencies. They are expecting candidates who can help in faster decision-making processes through their AI skills. Our Artificial Intelligence Online Course brings the following career advantages for the students enrolled in our Online AI Training Institute.
- Ability to work in the Data Analytics process as it is crucial for IoT and AI through skills like managing, analyzing, and data storage.
- Make way for working in User Experience with a specialization in the understanding of human interaction tools and equipment that help professionals to develop advanced software.
- Computer Science and AI Research is the field beneficial to AI and it makes the learners equipped with AI technologies for their innovations.
- AI is required for network engineering, planning, management, and support as they are very important for the companies on their network and IT infrastructure needs.
- Hardware Technologies are improved with AI-equipped processes and it ensures the protection and security of devices along with features like vulnerability evaluation, risk identity, public-key encryption security, and wireless communications.
- Natural Language Processing is the fastest-growing field with AI techniques and it creates tremendous opportunities for learners who are certified and skilled in system development.
Gain expertise on the industry-ready skills to obtain jobs easily in the above-mentioned industries by enrolling in our Online Artificial Intelligence Training Institute and we equip our students with fundamental engineering, mathematics, and statistics skills, OOPs concepts, compiler design, manufacturing, and industrial knowledge, web surfing technologies, operating system fundamentals, aptitude skills, soft skills, and interview strategies and tips until one gets placed.
The U.S Bureau of Labor Statics stated that the global employment in AI industries is growing 15% from 2019 to 2025 and it is projecting there will be 5,31,200 new jobs for the certified and skilled AI professionals for the global MNC and IT companies. Top companies like Walmart, MIT Lincoln, Amazon, IBM, Nike, Samsung Electronics America, Warner Bros Entertainment, Fidelity Investments, and Pepsico are hiring employees for their various profiles. We equip the students to work in the following job profiles through our Online AI Training Course at Softlogic.
- Artificial Intelligence Researcher
- Data Scientist
- Research Scientist
- Lead Artificial Intelligence Engineer
- Lead Machine Learning Engineer
- Conversational Artificial Intelligence Engineer
- Data Scientist
- Research Interns
- Customer Engineer
- Software Engineer
Our Online AI Course Certification adds value to your resume as it is globally recognized for its quality and performance. It validates your skills through a performance tracker and our trainers and placement coach will improve the areas to be focused on. We provide Artificial Intelligence Course Completion Certification at the end of the course and we update them in our placement portal for the companies’ reference. Enroll in our Online Artificial Intelligence Training Institute today to get the benefits.
Our Global Hiring Partners
Softlogic System is one of the leading platforms of Online Artificial Intelligence Training Institute with 100% Placement Assistance. Our AI Trainers are equipping 10000+ candidates every year with satisfying job placements and most of our learners are working in the following companies.
Deep Learning: A revolution in Artificial Intelligence
- Limitations of Machine Learning
- Need for Data Scientists
- Foundation of Data Science
- What is Business Intelligence
- What is Data Analysis
- What is Data Mining
Analytics vs Data Science
- Value Chain
- Types of Analytics
- Lifecycle Probability
- Analytics Project Lifecycle
- Advantage of Deep Learning over Machine learning
- Reasons for Deep Learning
- Real-Life use cases of Deep Learning
- Review of Machine Learning
- Basis of Data Categorization
- Types of Data
- Data Collection Types
- Forms of Data & Sources
- Data Quality & Changes
- Data Quality Issues
- Data Quality Story
- What is Data Architecture
- Components of Data Architecture
- OLTP vs OLAP
- How is Data Stored?
- What is Big Data?
- 5 Vs of Big Data
- Big Data Architecture
- Big Data Technologies
- Big Data Challenge
- Big Data Requirements
- Big Data Distributed Computing & Complexity
- Map Reduce Framework
- Hadoop Ecosystem
- What Data Science is
- Why Data Scientists are in demand
- What is a Data Product
- The growing need for Data Science
- Large Scale Analysis Cost vs Storage
- Data Science Skills
- Data Science Use Cases
- Data Science Project Life Cycle & Stages
- Data Acuqisition
- Where to source data
- Evaluating input data
- Data formats
- Data Quantity
- Data Quality
- Resolution Techniques
- Data Transformation
- File format Conversions
- Python Overview
- About Interpreted Languages
- Advantages/Disadvantages of Python pydoc.
- Starting Python
- Interpreter PATH
- Using the Interpreter
- Running a Python Script
- Using Variables
- Built-in Functions
- StringsDifferent Literals
- Math Operators and Expressions
- Writing to the Screen
- String Formatting
- Command Line Parameters and Flow Control.
- Indexing and Slicing
- Iterating through a Sequence
- Functions for all Sequences
- The xrange() function
- List Comprehensions
- Generator Expressions
- Dictionaries and Sets.
- Learning NumPy
- Introduction to Pandas
- Creating Data Frames
- Plotting Data
- Creating Functions
- Slicing/Dicing Operations.
- Function Parameters
- Global Variables
- Variable Scope and Returning Values. Sorting
- Alternate Keys
- Lambda Functions
- Sorting Collections of Collections
- Classes & OOPs
- What is Statistics
- Descriptive Statistics
- Central Tendency Measures
- The Story of Average
- Dispersion Measures
- Data Distributions
- Central Limit Theorem
- What is Sampling
- Why Sampling
- Sampling Methods
- Inferential Statistics
- What is Hypothesis testing
- Confidence Level
- Degrees of freedom
- what is pValue
- Chi-Square test
- What is ANOVA
- Correlation vs Regression
- Uses of Correlation & Regression
- ML Fundamentals
- ML Common Use Cases
- Understanding Supervised and Unsupervised Learning Techniques
- Similarity Metrics
- Distance Measure Types: Euclidean, Cosine Measures
- Creating predictive models
- Understanding K-Means Clustering
- Understanding TF-IDF, Cosine Similarity and their application to Vector Space Model
- Case study
- What is Association Rules & its use cases?
- What is Recommendation Engine & it’s working?
- Recommendation Use-case
- Case study
Decision Tree Classifier
- How to build Decision trees
- What is Classification and its use cases?
- What is Decision Tree?
- Algorithm for Decision Tree Induction
- Creating a Decision Tree
- Confusion Matrix
- Case study
- What is Random Forests
- Features of Random Forest
- Out of Box Error Estimate and Variable Importance
- Case study
- Case study
Problem Statement and Analysis
- Various approaches to solve a Data Science Problem
- Pros and Cons of different approaches and algorithms.
- Case study
- Introduction to Predictive Modeling
- Linear Regression Overview
- Simple Linear Regression
- Multiple Linear Regression
- Case study
- Logistic Regression Overview
- Data Partitioning
- Univariate Analysis
- Bivariate Analysis
- Multicollinearity Analysis
- Model Building
- Model Validation
- Model Performance Assessment AUC & ROC curves
- Case Study
- Introduction to SVMs
- SVM History
- Vectors Overview
- Decision Surfaces
- Linear SVMs
- The Kernel Trick
- Non-Linear SVMs
- The Kernel SVM
- Describe Time Series data
- Format your Time Series data
- List the different components of Time Series data
- Discuss different kind of Time Series scenarios
- Choose the model according to the Time series scenario
- Implement the model for forecasting
- Explain working and implementation of ARIMA model
- Illustrate the working and implementation of different ETS models
- Forecast the data using the respective model
- What is Time Series data?
- Time Series variables
- Different components of Time Series data
- Visualize the data to identify Time Series Components
- Implement ARIMA model for forecasting
- Exponential smoothing models
- Identifying different time series scenario based on which different Exponential Smoothing model can be applied
- Implement respective model for forecasting
- Visualizing and formatting Time Series data
- Plotting decomposed Time Series data plot
- Applying ARIMA and ETS model for Time Series forecasting
- Forecasting for given Time period
- Case Study
Machine learning algorithms Python
- Various machine learning algorithms in Python
- Apply machine learning algorithms in Python
- How to select the right data
- Which are the best features to use
- Additional feature selection techniques
- A feature selection case study
- Preprocessing Scaling Techniques
- How to preprocess your data
- How to scale your data
- Feature Scaling Final Project
- Highly efficient machine learning algorithms
- Bagging Decision Trees
- The power of ensembles
- Random Forest Ensemble technique
- Boosting – Adaboost
- Boosting ensemble stochastic gradient boosting
- A final ensemble technique
- Introduction Model Tuning
- Parameter Tuning GridSearchCV
- A second method to tune your algorithm
- How to automate machine learning
- Which ML algo should you choose
- How to compare machine learning algorithms in practice
- Sentimental Analysis
- Case study
- Introduction to Spark Core
- Spark Architecture
- Working with RDDs
- Introduction to PySpark
- Machine learning with PySpark – Mllib
Keras and TFLearn
- Transfer Learning Introduction
- Google Inception Model
- Retraining Google Inception with our own data demo
- Predicting new images
- Transfer Learning Summary
- Extending Tensorflow
- Keras vs TFLearn Comparison
- Deepening the network
- Images and Pixels
- How humans recognise images
- Convolutional Neural Networks
- ConvNet Architecture
- Overfitting and Regularization
- Max Pooling and ReLU activations
- Strides and Zero Padding
- Coding Deep ConvNets demo
- Debugging Neural Networks
- Visualising NN using Tensorflow
- Tensorflow data types
- CPU vs GPU vs TPU
- Tensorflow methods
- Introduction to Neural Networks
- Neural Network Architecture
- Linear Regression example revisited
- The Neuron
- Neural Network Layers
- The MNIST Dataset
- Coding MNIST NN
- Introducing Tensorflow
- Introducing Tensorflow
- Why Tensorflow?
- What is tensorflow?
- Tensorflow as an Interface
- Tensorflow as an environment
- Computation Graph
- Installing Tensorflow
- Tensorflow training
- Prepare Data
- Tensor types
- Loss and Optimization
- Running tensorflow programs
- Restricted Boltzmann Machine
- Applications of RBM
- Introduction to Autoencoders
- Autoencoders applications
- Understanding Autoencoders
- Building a Autoencoder model
- Recurrent neural networks rnn
- LSTMs understanding LSTMs
- long short term memory neural networks lstm in python
- Convolutional Operation
- Relu Layers
- What is Pooling vs Flattening
- Full Connection
- Softmax vs Cross Entropy
- ” Building a real world convolutional neural network for image classification”
- The Detailed ANN
- The Activation Functions
- How do ANNs work & learn
- Gradient Descent
- Stochastic Gradient Descent
- Understand limitations of a Single Perceptron
- Understand Neural Networks in Detail
- Illustrate Multi-Layer Perceptron
- Backpropagation – Learning Algorithm
- Understand Backpropagation – Using Neural Network Example
- MLP Digit-Classifier using TensorFlow
- Building a multi-layered perceptron for classification
- Why Deep Networks
- Why Deep Networks give better accuracy?
- Use-Case Implementation
- Understand How Deep Network Works?
- How Backpropagation Works?
- Illustrate Forward pass, Backward pass
- Different variants of Gradient Descent
Deep Learning & AI
- Case Study
- Deep Learning Overview
- The Brain vs Neuron
- Introduction to Deep Learning
Our Mentors are from Top Companies like
Take your career to new heights with Softlogic's software training certifications. Improve your abilities to get access to rewarding possibilities
A Proven Path to become a AI Engineer
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Aptitude Training from Day 1
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Panel Mock Interview
Interview Skills from Day 1
Build your Linked in Profile
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Softskills Training from Day 1
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The goal of Artificial Intelligence (AI) is to give machines the ability to "think like humans" by simulating their cognitive processes. Although artificial intelligence (AI) will never be as smart as a human being, it already has many practical uses.
Many factors have converged to make the present an exciting period for significant AI progress.
- Over the past 60 years, computing power has increased by a factor of a trillion, making it far more efficient than it was back then.
- Data processing is becoming more cost-effective.
- Businesses are collecting more signals from client encounters, which means there is more data to study.
- The use of AI has already greatly enhanced consumer apps, raising hopes for further greater simplification and hence increasing demand for AI expertise and research.
Absolutely to a greater extent. The vast majority of people who have access to a computer, smartphone, or other smart device are already making use of AI's practical benefits:
- Personal voice-processing assistants like Siri and Cortana are available now.
- Image recognition is highly recommended for use in Facebook photo tagging.
- Amazon uses machine learning algorithms to provide product recommendations.
- Waze uses a mix of predictive algorithms, forecasting, and optimisation approaches to recommend the best routes for drivers to take.
The most basic kind of Artificial Intelligence will help with automating routine operations. Businesses may save a lot of time and money by using automation to handle data collecting, sorting, entering, and transformation. As it develops, it will be able to forecast your company's future performance and tell you where you're succeeding.
In spite of "millions" of job openings, only roughly 300,000 people are working in artificial intelligence (AI). Programming expertise in Python, R, Java, and C++ are particularly in demand due to the widespread adoption of AI.
The World Economic Forum predicts that 97 million new employment will be produced by 2025 as a direct result of AI innovations, and this trend is expected to continue into the foreseeable future.
A wide variety of AI and Machine Learning tools and techniques are covered in our Artificial Intelligence training in Chennai. This course, developed by AI experts and aimed at developing professionals, is perfect for you if:
- Are a recent college graduate.
- Are contemplating a career change into artificial intelligence development.
- Have an interest in learning new skills to help you create, oversee, and organise AI-based solutions for your present company.
- Are looking for a way to continue their education at a higher level to improve their academic skills in this field.
At Softlogic Systems, you will receive hands-on experience and rigorous training from industry professionals. The course content covers both introductory and advanced-level material.
Learning from AI training in Chennai, which combines excellence and innovation, will provide you with abilities and expertise that are unique and essential in both your personal and professional lives.
When compared to competitors in the software training market, our placement services are unparalleled.
After successfully completing the Artificial Training in Chennai, you will, indeed, be awarded a certificate of completion for your efforts. Our certification is an IBM-accredited one, which gives more credence to your CV and helps you stand out more prominently throughout the interview process.
The placement support offered by Softlogic increases your chances of getting the job of your dreams. Certified students who are interested in making a career change or entering the workforce for the first time will have access to comprehensive assistance through our placement assistance. Softlogic will provide the following premium services as part of our placement assistance:
- Resume building
- Career Guidance and Advising
- Interview practise sessions
- Career Expos
Professionals that are skilled in artificial intelligence are in high demand across a wide range of organizations, including those of Google, Microsoft, Deloitte Accenture, IBM, Capgemini, Amazon, Apple, and many more MNCs.
As there is a rising demand for AI specialists but a shortage of people with the necessary abilities, businesses are prepared to pay greater wages for trained AI professionals. The following table displays, according to Payscale, the annual salary that an AI engineer earns on average in key nations:
- India - INR 982K
- Canada - C$ 85,000
- Australia - $110,000
- The US - $110K
- The UK - £60,000