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Module 1- Foundations of AI
Learning Objectives: Learn how to build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you. Develop expertise in popular AI & ML technologies and problem-solving methodologies. Develop the ability to independently solve business problems using Artificial Intelligence & Machine Learning
Module 2- Machine Learning : Supervised Learning
Learning Objectives:Learn about supervised learning techniques - regression and classification. Understand techniques to build Decision Trees
Hands-on: This dataset classifies people described by a set of attributes as good or bad credit risks. Using classification techniques, build a model to predict good or bad customers to help the bank decide on granting loans to its customers
Module 3- Machine Learning : Unsupervised Learning
Learning Objectives: Learn about unsupervised learning technique - K-Means Clustering and Hierarchical Clustering. Understand Elbow method and Silhouette method
Module 4- Machine Learning : Ensemble Techniques
Learning Objectives:Learn about bootstrap sampling and its advantages followed by bagging.Boost model performance with Boosting. Learn Random Forest with real-life case study and how it helps avoid overfitting compared to decision trees
Hands-on: In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. In this case study, use AdaBoost, GBM & Random Forest on Lending Data to predict loan status. Ensemble the output and see your result perform than a single model
Module 5- Machine Learning : Reinforcement Learning
Learning Objectives: Understand the basics of RL and its applications in AI. Markov Decision Processes: Model processes as Markov chains, learn algorithms for solving optimisation problems. Write Q-learning algorithms to solve complex RL problems.
Hands-on: No hands-on
Module 6- Deep Learning
Learning Objectives: Learn advanced machine learning techniques using the Neural Networks algorithms. Neural Networks can enable pattern recognition based on a large amount of inputs. Learn how NN algorithms work, and end up with an introduction to deep learning
Covers various activation functions like sigmoid, hyperbolic-tangent, Rectified Linear Units, Leaky Rectified Linear Units
Hands-on: The research aimed at the case of customers’ default payments in Taiwan. From the perspective of risk management, the result of predictive accuracy of the estimated probability of default will be more valuable than the binary result of classification - credible or not credible clients.
Module 7- Natural Language Processing
Learning Objectives: Get started with the Natural language toolkit, learn the basics of text processing in python. Learn how to extract features from unstructured text and build machine learning models on text data. Conduct sentiment analysis, learn to parse English sentences and extract meaning from them. Explore the applications of text analytics in new areas and various business domains.
Hands-on: Stock market prediction has been an interesting research topic for many years. Finding an efficient and effective means of studying the market perceptions found its way in different social networking platforms such as Twitter. With proper tools and the help of technology, meaningful and precious information can be gathered, analyzed, and utilized in different areas like in the movement and performance of the stock market.
Module 8- Computer Vision
Learning Objectives: Learn to use the power of computer vision and play with what you see, detect faces, eyes and other attributes using Haar cascades
Hands-on: While we drive on a highway, we tend to feel sleepy. In this project, using OpenCV and implementing object detection and feature extraction we detect fatigue in real-time and report an alarm which will not only keep a driver attentive while driving but also reduce number of accidents.
Module 9- Intelligent Agents
Learning Objectives: Learn the AI search technique that employs heuristic for its moves. Understanding the fundamental concepts of genetic algorithms and visualize the evolution
Hands-on: Use cutting edge AI techniques to teach a computer to play a computer game
Covers projects using Logistic Regression, Decision Tree, K-Nearest Neighbor, Neural Networks, Adaboost, GBM, Random Forest, Building game playing agent, Object Detection and Tracking using OpenCV
Attended a 2 day weekend course by Knowledgehut for the CSM certification. The instructor was very knowledgeable and engaging. Excellent experience.Attended workshop in April 2018
The CSPO Training was awesome and great. The trainer Anderson made all the concepts look so easy and simple. Using his past experience as examples to explain various scenarios was a plus. Moreover, it was an active session with a lot of participant involvement which not only made it interactive but interesting as well. Would definitely recommend this Training.Attended workshop in July 2018
Great course. An interesting and interactive session to better understand how to succeed in formulating a business case and how to present it effectively.Attended workshop in May 2018
The training was very interactive and engaging with the attendees.Attended workshop in June 2018
Artificial intelligence is the technology of making our systems more intelligent and providing solutions to problems. AI is the hottest career in this digital age and AI experts certainly earn the big bucks. According to Neuvoo, the average salary for Artificial Intelligence related jobs is $73,552 per year or $38 per hour. This is around 2.5 times more than the average salary in America. This course will help you understand the core concepts of AI and use it to build intelligent solutions. You will also get in-depth prep help to clear interviews and land jobs.
On completing this course you will:
By the end of this course, you will gain
There are no restrictions but participants would benefit if they have sound knowledge in Python and familiarity with Data Science.
Yes, KnowledgeHut offers this training online.
On successful completion of the course you will receive a course completion certificate issued by KnowledgeHut
Your instructors are AI experts who have years of industry experience.
Any registration cancelled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding) Refunds will be processed within 30 days of receipt of written request for refund. Kindly go through our Refund Policy for more details: http://www.knowledgehut.com/refund
KnowledgeHut offers a 100% money back guarantee if the candidate withdraws from the course right after the first session. To learn more about the 100% refund policy, visit our
In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience
Minimum Requirements: MAC OS or Windows with 8 GB RAM and i3 processor