Ai ARTIFICIAL INTELLIGENCE
Specialization | 7 Course Series | 3 Mock Tests
This Online Artificial Intelligence Certification includes 7 courses with 49+ hours of video tutorials and One year access and several mock tests for practice. This training covers deep learning, machine learning, and data science practices to make you an AI expert.
Offer ends in:
What you'll get
- 49+ Hours
- 7 Courses
- Mock Tests
- Course Completion Certificates
- One year access
- Self-paced Courses
- Technical Support
- Mobile App Access
- Case Studies
- Download Curriculum
Synopsis
- Courses: You get access to all 7 courses, Projects bundle. You do not need to purchase each course separately.
- Hours: 49+ Video Hours
- Core Coverage: Artificial Intelligence& Machine Learning, Ensemble Learning, Decision Trees with R and Python
- Course Validity One year access
- Eligibility: Anyone serious about learning Artificial Intelligence and wants to make a career in this Field
- Pre-Requisites: Basic knowledge of Artificial Intelligence would be preferable
- What do you get? Certificate of Completion for each of the 7 courses, Projects
- Certification Type: Course Completion Certificates
- Verifiable Certificates? Yes, you get verifiable certificates for each course with a unique link. These links can be included in your resume/LinkedIn profile to showcase your enhanced data analytics skills
- Type of Training: Video Course – Self-Paced Learning
Content
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MODULE 1: Introduction to Artificial Intelligence with Python
Courses No. of Hours Certificates Details Artificial Intelligence with Python - Beginner Level 2h 51m ✔ Artificial Intelligence with Python - Intermediate Level 4h 34m ✔ AI Artificial Intelligence & Predictive Analysis with Python 6h 15m ✔ -
MODULE 2: Advanced Artificial Intelligence and Machine Learning
Courses No. of Hours Certificates Details Artificial Intelligence and Machine Learning Training Course 12h 13m ✔ Machine Learning with R 20h 25m ✔ -
MODULE 3: Specialized Topics in Machine Learning with R
Courses No. of Hours Certificates Details Logistic Regression & Supervised Machine Learning in Python 2h 6m ✔ Project on R - Card Purchase Prediction 2h 28m ✔ -
MODULE 4: Mock Tests and Quizzes
Courses No. of Hours Certificates Details Test - AI Artificial Intelligence with Python Minor Test 1 Test - AI Artificial Intelligence with Python Minor Test 2 Test - AI Artificial Intelligence with Python Major Test
Description
Course Introduction: Comprehensive Artificial Intelligence and Machine Learning Mastery
Welcome to our comprehensive course on Artificial Intelligence (AI) and Machine Learning (ML), designed to provide you with a thorough understanding of these cutting-edge technologies. Throughout this course, you will embark on an exciting journey into the world of AI and ML, exploring fundamental principles, advanced techniques, and practical applications using Python and R programming languages.
Section 1: Introduction to Artificial Intelligence with Python
In Section 1, we lay the foundation for your AI journey with two courses: "Artificial Intelligence with Python - Beginner" and "Artificial Intelligence with Python - Intermediate." These courses introduce you to key AI concepts and techniques, including neural networks, natural language processing, and computer vision, using the versatile Python programming language.
Section 2: Advanced Artificial Intelligence and Machine Learning
Section 2 dives deeper into advanced topics in AI and ML. The course "Artificial Intelligence and Machine Learning" provides an in-depth exploration of cutting-edge techniques such as deep learning and reinforcement learning. Through hands-on exercises and real-world projects, you will gain the skills and expertise needed to develop intelligent systems and solve complex problems.
Section 3: Specialized Topics in Machine Learning with R
Section 3 focuses on machine learning using the R programming language. The course "Machine Learning with R" offers a comprehensive overview of machine learning algorithms, with a particular emphasis on logistic regression and supervised learning. You will also work on a practical project, "Project on R - Card Purchase Prediction," to apply your knowledge in a real-world scenario.
Section 4: Mock Tests and Quizzes
In the final section, you will have the opportunity to assess your understanding and proficiency through mock tests and quizzes. These assessments cover the material taught in the previous sections, allowing you to evaluate your knowledge and identify areas for improvement. By completing these tests, you will solidify your understanding of AI and ML concepts and prepare yourself for future challenges in the field.
Throughout this course, our goal is to provide you with a comprehensive understanding of AI and ML, equipping you with the skills and knowledge needed to succeed in this rapidly evolving field. Whether you're a beginner or an experienced professional, there's something for everyone in this course. Let's embark on this exciting journey together!
Sample Certificate
Requirements
- Basic Programming Knowledge: A fundamental understanding of programming concepts is recommended, including variables, loops, conditionals, and functions. Proficiency in Python and R programming languages would be advantageous.
- Mathematics Foundation: Familiarity with foundational mathematics concepts such as algebra, calculus, and statistics is essential. Understanding linear algebra (vectors, matrices) and probability theory will facilitate comprehension of machine learning algorithms.
- Python and R Proficiency: Prior experience with Python and R programming languages is beneficial but not mandatory. If you're new to these languages, consider completing introductory courses or tutorials to familiarize yourself with their syntax and features.
- Statistical Knowledge: Basic knowledge of statistics, including descriptive statistics (mean, median, mode), probability distributions, and hypothesis testing, is recommended. This will aid in understanding the statistical principles underlying machine learning algorithms.
- Machine Learning Fundamentals: While not required, familiarity with fundamental machine learning concepts such as supervised learning, unsupervised learning, and model evaluation will be helpful. Online resources or introductory courses can provide an overview of these concepts if needed.
- Curiosity and Eagerness to Learn: An open mindset and willingness to explore new concepts and technologies are essential prerequisites. Machine learning and artificial intelligence are dynamic fields with continuous advancements, so a curious attitude and eagerness to learn are crucial for success in this course.
Target Audience
- Aspiring Data Scientists: Individuals aiming to pursue a career in data science and machine learning, seeking comprehensive training to acquire the necessary skills and knowledge.
- Software Developers: Developers interested in expanding their expertise to include artificial intelligence and machine learning, enhancing their career prospects and ability to work on AI-driven projects.
- Students and Academics: Students studying computer science, data science, mathematics, engineering, or related fields, looking to supplement their academic curriculum with practical training in AI and ML.
- Professionals Seeking Career Transition: Professionals from diverse backgrounds interested in transitioning to roles in AI, ML, or data science, seeking to acquire relevant skills and pivot their career trajectories.
- Entrepreneurs and Business Owners: Entrepreneurs and business owners looking to leverage AI and ML technologies to innovate, optimize business processes, and gain a competitive edge in their respective industries.
- Professionals Seeking Skill Enhancement: Professionals already working in the fields of data science, machine learning, or artificial intelligence, aiming to deepen their expertise and stay updated with the latest advancements in the field.
- Technology Enthusiasts: Individuals with a keen interest in emerging technologies and a desire to explore the possibilities of artificial intelligence and machine learning in various domains.
- Anyone Curious about AI and ML: Individuals curious about artificial intelligence and machine learning, regardless of their background or current occupation, interested in gaining a foundational understanding of these transformative technologies.
Course Ratings
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The course covers a wide range of areas into linear and multiple linear regression and decision tress. It also covers both theory and application using R neural network , time series analysis and gradient boosting machines. I have enjoyed learning in this course very much and found it useful in my work.
Tsui Man Kit
I really enjoyed all the videos in this training, the level its high and complex, I had to stop and replay many videos to clearly get all the information provided, and it took me over a 2 weeks to truly go over all the videos. A lot of the information I knew due to my technical background but there was so much material that the amount of new information it’s a bit overwhelming. Great job for the team that put this together.
Jorge Dominguez
This was a really interesting course. I had prior knowledge regarding data analytics, including descriptive, prescriptive and predictive modelling using various tools, but this course was different. This taught me a lot of things which I did not know as a person who was good in statistics and probability. Overall the course was Good.
Keerthi Vasan
Thanks team for this awesome set of videos on Artificial Intelligence and Machine Learning. Found it really useful, specifically from the placement point of view. Now I have a good overview about the subject.I believe it would be beneficial for all students who are interested to know more about AI&ML.
Rakesh Mohan Mohapatra