Advanced Program in Artificial Intelligence and Machine Learning
The AI-ML program covers essential topics like Statistics, Machine Learning, Deep Learning, Natural Language Processing, and Reinforcement Learning. Live sessions by global practitioners, labs, and industry projects are all incorporated into this program through our interactive learning model. Aims at acquiring industry-valued skills and the most commonly used tools and techniques.

Monthly Recurring Batch

Program Duration

12 Months

Learning Format

Blended Learning

Program Fees

$3750

Course Overview

Artificial Intelligence course is designed for C-suite leaders and founders who are looking for ways to set their business up for future success., who want to use the power of EI to improve AI outputs in their organizations. Digital experts who want to get more out of their existing AI outputs also stand to benefit greatly from the course.This course covers understanding of extended intelligence and to apply Big Data and AI techniques to business scenarios. Also focusses on actionable frameworks for creating human-compatible AI systems.

Training Key Features

For More Information

    What you will learn

    About Acacia University Extension (AUX)

    AUX, an extension of the prestigious Acacia University, USA, has initiated various programs in partnership with Airtics Education. The wide range of programs aims to upskill millions of students in trending technologies through a blend of theoretical and hands-on knowledge and are taught by leading academicians.

    Upon completion of these programs, you will receive an Advanced Certification from AUX.

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    Skills Covered

    Machine Learning

    Deep Learning

    Natural Language processing

    Reinforcement Learning

    Computer Vision

    Neural Networks

    Who Can Apply for the Course?

    Tools/ Frameworks/ Libraries

    Scripting tools

    Python, R

    Tools/Libraries

    Pandas,numPy,seaborn,matploltlib,cufflinks,scikit, NLTK, CoreNLP, spaCy, PyNLP,Flask

    IDE shell

    Jupyter Notebook, google colab, pycharm, visualstudio code

    Automated Machine Learning Models

    Supervised, Unsupervised, Reinforced learnings

    Application And Use Cases

    Financial trading
    Marketing personalization
    Recommendations
    Online search
    NLP-Natural language preprocessing
    Recommendations
    Predictive analytics
    Forecasting trends

    Eligibility

    Firm knowledge of software fundamentals with data structures, linear programming and architecture is beneficial. Candidates from programming and non programming background could also opt for this in-demand course.

    Prerequisites

    Due to its involvement in modern Machine Learning algorithms with math and programming, candidates having knowledge with linear algebra, probability and calculus could be a plus.

    Course Modules

    Topics Covered: Data Science, Mathematics, Python Programming, Data Analytics Visualization, Machine Learning, Artificial Intelligence, Business Intelligence-Powerbi, Database Management.
    • basics, conditional statements, loops
    • lists, tuples, dictionaries, sets
    • functions, classses
    • Hands on Numpy
    • Hands on Pandas
    • Exploratory data analysis, Matplotlib and Seaborn
    • Measures of central tendency and variation
    • Hypothesis testing (z-test, t-test, anova)
    • Probability and distributions
    • Handling Missing values, outliers
    • One hot encoding, standization and normalization
    • Python ML pipelines
    • Supervised ML
    • Regression, Logistic regression, KNN, SVM, Naive Bayes
    • Decision Trees, Ensemble Learning (random forests, gradient boosting)
    • Use case supervised learning
    • KMeans clustering
    • Hierarchical clustering
    • Use case unsupervised learning
    • Introduction to convolutional Neural networks
    • Image classification using CNN
    • Image Segmentation techniques

    • Regular expressions, NLTK, Spacy, Gensim
    • Tokenization, POS tagging, stopword removal, steemming, lemmtization
    • NER and custom NER
    • Latent Sementic Indexing
    • LDA
    • USe case for topic modelling
    • Flask Framework
    • HTML and CSS, data bases
    • Integration/ Hosting an ML application

    Interested in This Program? Secure your spot now.

    The application is free and takes only 5 minutes to complete.

      Student Reviews

      Veeraiah Yadav Doddaka
      IT Manager, Samsung

      I choose to learn Data Science and explored many options on which institute to join, among that what I found is Airtics as the best in terms of the course curriculum/on line content they designed and most…..

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      Prasad Joshi
      RF Optimization Engineer, Nokia

      I was a Data Science student at Airtics Education, which helped build a solid data science background and sharpen my programming skills…

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      Mohamed Hanan
      Procurement Assistant

      The program in Data Science offered by Airtics Education is rigorous and has provided me with a greater understanding of the data science world…

      Read More

      Capstone Projects

      House rental Prediction

      Image Classification

      Business insights reporting

      Career Support

      Frequently Asked Questions

      With the pace that every industry is introducing Artificial intelligence in their domain, Learning this course will open up a world of opportunities to create point and innovative technologies in diverse sectors.

      We provide you live recorded classes of the same session to follow up, if you end up missing the same.

      Data science and machine learning are a subset of artificial intelligence. The purpose of data science and ml is to reach to the point of AI. That the machine should start thinking or make decision like human being. AI requires a continuous feed of data to learn and improve decision-making

      Accelerated Artificial intelligence career guidance with world class training on the most in-demand Data science and Machine learning skills. Training and hands-on experience with key tools and technologies including Python,PowerBi and concepts of Machine Learning, statistics, natural language preprocessing, deep learning, computer vision and more. Upon completing the course you will be receiving _____ certificate from ________

      Aspirants, professionals and who is having basic computer programming skills  can enroll for the course

      Basic knowledge of programming logic and technology exposure will be helpfull.

      For Machine learning, you should be good at Linear Algebra, Multivariate Calculus, Probability, and Statistics.

      Python is in the first place, especially for beginners. But if you are well versed in Machine Learning, then you can learn the R Programming language.

      Big NO!. In machine learning, you need to build a machine learning model. And to build a model, you should know programming.

      What is included in this course?

      I’m Interested in This Program

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        Course Preview

        Advanced Program in Artificial Intelligence and Machine Learning


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