Machine Learning and AI

In this Machine Learning And AI Course, you will learn Python, Regression Algorithms, Database and SQL, Mathematical Foundation, Statistical Methods, Data Visualization, Classification Algorithms, Deep Learning, Unsupervised Algorithms, Big Data, Time Series, Natural Language Processing & more.

skill9-machine-learning-and-ai

Learn Artificial Intelligence & Machine Learning from the basics to advanced concepts, including Inferential Statistics, A/B Testing, Regression, Clustering, Decision Trees, Random Forests and more

Course Brochure

  • For whom this Course is meant?

    ✔ Designed for any undergraduates or job seekers and professionals who want to enhance their technical knowledge.
    ✔ Studying/Studied GRADUATION.
    ✔ Any Graduate/engineer who is interested in Coding.
    ✔ Freshers/Graduates.
    ✔ Non-programming engineers.

  • Why take this course?

    ✔ This course is blended with IT industry experience where even a fresher can start working on projects in the IT industry easily.
    ✔ This Course gives desired knowledge on coding which is the entry-level criteria for any interview.
    ✔ Affordable Fee Structure.

  • In addition, this course helps you

    ✔ Improve your logical thinking: Improve your problem-solving abilities.
    ✔ Improve your searching skills: Understand how software applications work.
    ✔ Find a nice and well-paid job: Improve your self-confidence.
    ✔ 100% JOB ASSISTANCE after completion of the course to make your Profile reach Hundreds of Recruiters in our network and with the company we have tied up.

DDL, DML, DQL statements
Aggregate, Date Functions
Union, Union All & Intersect Operators
Joins
Views & Indexes
Sub-queries
Introduction
Python Objects, List
Functions
Numpy
Pandas
Data Frame Manipulation
Data Visualization
EDA
Introduction
Introduction to Statistics
Probability Theory
Probability Distributions
Hypothesis Testing
Statistical Tests
Introduction to Machine Learning
Types of Machine Learning
Linear Regression
Optimization Techniques
Gradient Descent
Logistic Regression
Model tuning
Decision Trees
Random Forests
K-Means CLustering
Hierarchical Clustering
Principal Components Analysis (PCA)
Time Series
Neural Network
Keras
Tensorflow
Convolutional Neural Network (CNN)
Recurrent Neural Network (RNN)
Applications of Deep Learning
Introduction to AI
Text Analytics & Natural Language Processing (NLP)
NLTK
Image processing & Computer Vision
OpenCV
Applications of AI
Introduction
Introduction to Tableau
Tableau Interface and Chart Types
Visual Analytics with Tableau
Dashboard and Stories
Advanced Machine Learning
Machine Learning Projects
Advanced AI
AI Projects
Advanced Machine Learning
Machine Learning Projects
Deep Learning Projects