Certified Python (AI) Developer (CPD) Training

The Certified Python (AI) Developer (CPD) training focuses on delivering an overview of artificial intelligence (AI) principles and approaches in industry based on best practices. In this course, you will get to learn the application of classical models used in Machine Learning and Deep Learning in terms of quality parametric would be addressed using both APIs and Python.

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  127 Ratings

               329 Participants

Group Discount

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40 hours (5 days) training

GICT Authorized Training Partner

Intermediate-level Artificial Intelligence Course

Hands-on Labs with AI Tools

Certified Python (AI) Developer (CPD) Course Description


This Certified AI Python Developer course is aimed at training candidates on the implementation of one of the latest APIs in AI, with a focus on Tensor Flow. The certification also leverages an intuitive approach to build complex models with human-like intelligence that will help solve real-world problems using Machine Learning and Deep Learning techniques.

Technologies such as deep learning, intelligent robots, and neuro-linguistic programming under Artificial Intelligence have been aiding in the enhancement of the existing computing systems to produce high-value predictions.

This 5-day training is inclusive of training and exam.

Course Curriculum


Audience

  • Senior Data Engineer
  • Cloud Architect
  • Data Scientist
  • Business Analyst
  • Dev Ops Engineer
  • Applications Developer
  • IHL students

Course Objectives

  • To present an overview of artificial intelligence (AI) principles and approaches in industry based on best practices.
  • To understand application of classical models used in Machine Learning and Deep Learning in terms of quality parametric would be addressed using both APIs and Python.
  • To understand to build intelligent computing models in Anaconda Jupyter Notebook.

Eligibility Criteria

Participants are preferred to have experience in software development or business analysis.

About The Examination

This is a 5-day intensive training program with the following assessment components.

Component 1. Written Examination

Component 2. Project Work Component (PWC)

These components are individual based. Participants will need to obtain 70% in both the components in order to qualify for this certification.

Course Benefits

The global artificial intelligence market is expected to reach USD 35,870.0 million by 2025 from its direct revenue sources, growing at a CAGR of 57.2% from 2017 to 2025. And the Deep Learning market in particular is expected to be worth USD 1772.9 Million by 2022, growing at a CAGR of 65.3% between 2016 and 2022.

Considering these facts and figures, the Certified Python (AI) Developer course is definitely a great certification to boost your career prospects.

Scope

  • Introduction to AI and its applications
  • Python Programming Fundamentals
  • Python for data preprocessing & wrangling
  • NoSQL databases and Applications of MongoDB
  • MongoDB Fundamentals
  • AI Categories & Feature Engineering
  • Convolutional Neural Networks & its applications
  • AI with Python using NLTK

As part of the written examination, each participant will be assessed individually on the last day of the training for their understanding of the subject matter and ability to evaluate, choose and apply them in specific context and also the ability to identify and manage risks.

The assessment focuses on higher levels of learning in Bloom’s taxonomy: Application, Analysis, Synthesis and Evaluation.

This written examination will primarily consist of 40 multiple choice questions spanning various aspects as covered in the program. It is an individual, competency-based assessment.

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Training Options


ONLINE TRAINING

Instructor led Online Training


  • 40 hrs (5 days) inclusive of training and exam
  • Experienced Subject Matter Experts
  • Approved and Quality Ensured training Material
  • 24*7 leaner assistance and support

CORPORATE TRAINING

Customized to your team's need


  • Blended Learning Delivery Model (Self-Paced E-Learning And/Or Instructor-Led Options)
  • Course, Category, And All-Access Pricing
  • Enterprise-Class Learning Management System (LMS)
  • Enhanced Reporting For Individuals And Teams
  • 24x7 Teaching Assistance And Support

Course Outline


  • Introduction to AI
  • Goals and applications AI
  • Differences between AI, ML & DL
  • Classification of AI algorithms
  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • Advantages of Python & Program execution
  • Variables and assignments
  • Data types
  • Control Flow- Logical Comparisons , Boolean Conditionals
  • Looping Constructs
  • Functions and Function Arguments
  • Object-oriented programming in Python
  • Dictionaries, Sets, Classes, Inheritance
  • Introduction to Packages
  • Packages Cheat Sheet.
  • Implementation using
  • Regression.
  • Linear Regression model using Numpy and Matplotlib.
  • Classification.
  • Explore Classification Algorithms.
  • Clustering
  • K Means
  • Introduction to Databases
  • Basic of NoSQL
  • Categories of NoSQL Databases
  • Hands On
  • Download and Installation (Server and Cloud based)
  • Explore MongoDB Atlas Analytics features
  • Basic, Intermediate and Advanced SQL commands
  • PyMongo
  • Keras Core defined. Hello World
  • Keras implementation. Image Classification
  • Build a Neural Network to do Classification.
  • Train-Test Neural Network.
  • Evaluate the model.
  • Lets draw a flow chart of the major steps.
  • Define factors that can influence a Good Fit.
  • Review the Classification Reports.
  • Introduction to Text Analytics.
  • Classification
  • Tokenization
  • Stopwords
  • Stemming,
  • Tagging
  • Parsing
  • Semantics
  • Lemmatization,
  • Application of Sentiment Analysis
  • Bag of Words, TF-IDF, Word Embeddings.
  • Logistics, SVM, Random Forest.
  • The future of BoT today.
  • Eliza, the Rogerian Therapist
  • Implementation of a simple BoT program.
  • Implementation of a GUI Chatbot using Python.
  • Security Defined.
  • Top 10 Reasons and Fixes of Security issues.
  • The Pickle API Case study.
  • Programmers Guide to addressing security issues.
  • Cisco’s perspective of Cognitive Challenges in AI.

 

Participants will have guided hands-on sessions on building Machine Learning and Deep Learning models. During this session they will gain understanding of several algorithms in building a successful intelligent computing system.

Hands-on 1: Programming Python using Tensorflow, Keras and Pytorch.

Hands-on 2: Benchmark Machine Learning models (ML) using APIs.

Hands-on 3: Optimization of a Keras CNN based on Cost-Losss.

Hands-on 4: Text Processing using NTLK

Course Reviews


FAQ's


Vinsys is a reliable training organization for professional certification courses such as the AI CPD course. We have matured over 21 years of our training journey and have a proud history of successfully certifying 750,000+ professionals globally. Our GICT approved trainers and courseware are updated as per the latest industry guidelines to provide the best of learning experience to our students.

Though there are no formal requirements for the AI CPD course, participants are preferred to have experience in software development or business analysis.

The Certified Python (AI) Developer training involves the following tools/software:

  • Python
  • Tensorflow
  • Keras
  • Pytorch
  • Natural Language Toolkit (NTLK)

Yes, definitely. Artificial Intelligence is an exciting and innovative area of technology that has seamless possibilities to explore. It is one of the most sought-after certification technologies curious minds of today aspire to earn. The Certified Python AI Developer course is definitely a great investment.