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This Advanced program in Artificial Intelligence will help you become competent in various aspects of AI, such as Machine Learning with Python, Artificial Neural Networks, Deep Learning with TensorFlow, and several other advanced concepts, through real-time projects. On completion of the program, you will receive PLA Credits from Belhaven University.
Learning Format
Online
Duration
198 Hours
Career Services
by Intellipaat
12 PLA Credits from
Belhaven University
400+
Hiring Partners
In this Advanced program in Artificial Intelligence, you will master the core concepts in AI along with various tools and technologies in the domain. The program has over 10 courses and 24 industry-based projects that will translate to practical experience in the domain.
About Belhaven University
Belhaven University is known for its nationally recognized academics, top-rated faculty, and affordability. Belhaven strives for excellence in higher education and has achieved prominence in education dating back to 1883. At Belhaven, every student is encouraged to develop and grow to the best of their potential.
Key achievements of Belhaven University:
Upon the completion of this program, you will:
57% Average Salary Hike
$1,14,000 Highest Salary
12000+ Career Transitions
300+ Hiring Partners
Career Transition Handbook
*Past record is no guarantee of future job prospects
Develop strategies on technologies, frameworks, and infrastructure that could help in creating AI solutions.
Assess and validate AI models using tuning and model fit testing.
Develop robust optimization algorithms for numerous applications built on AI.
Use Machine Learning tools and techniques to create statistical models consisting of large volumes of data.
Scale and prototype the latest Machine Learning and AI solutions in the cloud environment in order to meet business requirements.
Skills to Master
Artificial Intelligence using Python
Data Science with R
Machine Learning
Business Analytics
Business Intelligence
TSA
SVM
Neural Networks
Graph Visualization
Keras
Deep Learning with TensorFlow
Excel
Tableau
AWS Big Data
Tools to Master
42 Hours 15 Module
Module 01 – Introduction to Data Science with R
Module 02 – Data Exploration
Module 03 – Data Manipulation
Module 04 – Data Visualization
Module 05 – Introduction to Statistics
Module 06 – Machine Learning
Module 07 – Logistic Regression
Module 08 – Decision Trees and Random Forest
Module 09 – Unsupervised Learning
Module 10 – Association Rule Mining and Recommendation Engines
Module 11 – Introduction to Artificial Intelligence
Module 12 – Time Series Analysis
Module 13 – Support Vector Machine (SVM)
Module 14 – Naïve Bayes
Module 15 – Text Mining
42 Hours 12 Module
Module 01 – Python Environment Setup and Essentials
Module 02 – Python language Basic Constructs
Module 03 – OOP concepts in Python
Module 04 – Database connection
Module 05 – NumPy for mathematical computing
Module 06 – SciPy for scientific computing
Module 07 – Matplotlib for data visualization
Module 08 – Pandas for data analysis and machine learning
Module 09 – Exception Handling
Module 10 – Multi Threading & Race Condition
Module 11 – Packages and Functions
Module 12 – Web scraping with Python
32 Hours 9 Module
Module 01 – Introduction to Machine Learning
Module 02 – Supervised Learning and Linear Regression
Module 03 – Classification and Logistic Regression
Module 04 – Decision Tree and Random Forest
Module 05 – Naïve Bayes and Support Vector Machine (self-paced)
Module 06 – Unsupervised Learning
Module 07 – Natural Language Processing and Text Mining (self-paced)
Module 08 – Introduction to Deep Learning
Module 09 – Time Series Analysis (self-paced)
32 Hours 13 Module
Module 01 – Introduction to Deep Learning and Neural Networks
Module 02 – Multi-layered Neural Networks
Module 03 – Artificial Neural Networks and Various Methods
Module 04 – Deep Learning Libraries
Module 05 – Keras API
Module 06 – TFLearn API for TensorFlow
Module 07 – Dnns (deep neural networks)
Module 08 – Cnns (convolutional neural networks)
Module 09 – Rnns (recurrent neural networks)
Module 10 – Gpu in deep learning
Module 11 – Autoencoders and restricted boltzmann machine (rbm)
Module 12 – Deep learning applications
Module 13 – Chatbots
20 Hours 6 Module
Module 01 – Overview of Natural Language Processing and Text Mining
Module 02 – Text Mining, Cleaning, and Pre-processing
Module 03 – Text Classification
Module 04 – Sentence Structure, Sequence Tagging, Sequence Tasks, and Language Modeling
Module 05 – Introduction to Semantics and Vector Space Models
Module 06 – Dialog Systems
32 Hours 10 Module
Module 01 – Introduction to Big Data and Data Collection
Module 02 – Introduction to Cloud Computing & AWS
Module 03 – Elastic Compute and Storage Volumes
Module 04 – Virtual Private Cloud
Module 05 – Storage – Simple Storage Service (S3)
Module 06 – Databases and In-Memory DataStores
Module 07 – Data Storage
Module 08 – Data Processing
Module 09 – Data Analysis
Module 09 – Data Visualization and Data Security
24 Hours 23 Module
Module 01 – Entering Data
Module 02 – Referencing in Formulas
Module 03 – Name Range
Module 04 – Understanding Logical Functions
Module 05 – Getting started with Conditional Formatting
Module 06 – Advanced-level Validation
Module 07 – Important Formulas in Excel
Module 08 – Working with Dynamic table
Module 09 – Data Sorting
Module 10 – Data Filtering
Module 11 – Chart Creation
Module 12 – Various Techniques of Charting
Module 13 – Pivot Tables in Excel
Module 14 – Ensuring Data and File Security
Module 15 – Getting started with VBA Macros
Module 16 – Ranges and Worksheet in VBA
Module 17 – IF condition
Module 18 – Loops in VBA
Module 19 – Debugging in VBA
Module 20 – Dashboard Visualization
Module 21 – Principles of Charting
Module 22 – Getting started with Pivot Tables
Module 23 – Statistics with Excel
30 Hours 13 Module
Module 01 – Introduction to Data Visualization and The Power of Tableau
Module 02 – Architecture of Tableau
Module 03 – Charts and Graphs
Module 04 – Working with Metadata and Data Blending
Module 05 – Advanced Data Manipulations
Module 06 – Working with Filters
Module 07 – Organizing Data and Visual Analytics
Module 08 – Working with Mapping
Module 09 – Working with Calculations and Expressions
Module 10 – Working with Parameters
Module 11 – Dashboards and Stories
Module 12 – Tableau Prep
Module 13 – Integration of Tableau with R
The projects are well-suited for learners who want to gain industry experience and hands-on training in the domain.
Practice 100+ Essential Tools
Designed by Industry Experts
Get Real-world Experience
Total Admission Fee
Date | Time | Batch Type | |
---|---|---|---|
Regular Classes | 16th Nov 2024 | 08:00 PM IST | Weekend (Sat - Sun) |
This online Advanced program is designed to help you gain hands-on experience in the Artificial Intelligence domain and become a successful AI professional. The various courses meet industry standards and requirements. By the end of the program, you will have a strong background in the various skill sets and tools that are in demand in the corporate world. After completing the program, you will receive PLA Credits from Belhaven University.
You will also get the opportunity to work on several projects and assignments that are relevant to the real-industry environment. On completion of the program, you will be qualified to apply for some of the top-paying jobs around the world.
You can start by signing up for our Advanced program in AI. Once you successfully complete the program, as well as the projects and assignments, you will receive your PLA Credits from Belhaven University.
Our Learning Management System (LMS) provides a customized learning experience with live sessions as well as self-paced videos. If you miss a live session for any reason, you will be able to watch the recorded version of the session without having to worry about missing the lesson.
You can get in touch with our course advisors for more information. They will provide you with all the assistance you need.
Belhaven University PLA Credits Assessed for this course is 12.
*Note, there is a maximum number of PLA credits that may be applied toward a degree program. Refer to the Belhaven University website for the latest on PLA policies.
Please note that the course fees is non-refundable and we will be at every step with you for your upskilling and professional growth needs.
Due to any reason you want to defer the batch or restart the classes in a new batch then you need to send the batch defer request on [email protected] and only 1 time batch defer request is allowed without any additional cost.
Learner can request for batch deferral to any of the cohorts starting in the next 3-6 months from the start date of the initial batch in which the student was originally enrolled for. Batch deferral requests are accepted only once but you should not have completed more than 20% of the program. If you want to defer the batch 2nd time then you need to pay batch defer fees which is equal to 10% of the total course fees paid for the program + Taxes.
Yes, Intellipaat certification is highly recognized in the industry. Our alumni work in more than 10,000 corporations and startups, which is a testament that our programs are industry-aligned and well-recognized. Additionally, the Intellipaat program is in partnership with the National Skill Development Corporation (NSDC), which further validates its credibility. Learners will get an NSDC certificate along with Intellipaat certificate for the programs they enroll in.
What is included in this course?