3 in 1 AI Internship Combo

3 in 1 AI Internship Combo

Artificial Intelligence + Machine Learning + Data Analytics

What you will learn

Internship in Artificial Intelligence :

Artificial Intelligence

• Overview of this course | Introduction to AI | How to create basic AI application (Chat bot using DialogFlow)
• How to install Python & Libraries | Basics of Python Programming for AI

Computer Vision

• Introduction to Computer Vision| How to install computer vision libraries
• Moving Object Detection and tracking using OpenCV
• Face Detection and Tracking using OpenCV
• Object Tracking based on color using OpenCV
• Face Recognition using OpenCV
• Face Emotion recognition using 68-Landmark Predictor OpenCV

Deep Learning

• Introduction to Deep Learning | How to install DL libraries
• Designing your First Neural Network
• Object recognition from a Pre-trained model
• Image classification using Convolutional Neural Network
• Hand gesture recognition using Deep Learning
• Leaf disease detection using Deep Learning
• Character recognition using Convolutional Neural Network
• Label reading using Optical Character Recognition
• Smart Attendance System Using Deep Learning
• Vehicle detection using Deep Learning
• License plate recognition using Deep Learning
• Drowsiness detection using Deep Learning
• Road sign recognition using Deep Learning

Machine Learning

• Introduction to Machine Learning | How to install ML libraries
• Evaluating and Deploying the various ML model
• Fake news detection using ML
• AI snake game design using ML

Natural Langage Processing

• Introduction to NLP & its Terminology | How to install NLP Libraries NLTK
• Title Formation from the paragraph design using NLP
• Speech emotion analysis using NLP

Deploying AI in Hardware

• Cloud-based AI, Object recognition using Amazon Web Service (AWS) & Imagga
• Deploying AI application in Raspberry Pi with Neural Compute stick & Nvidia Jetson Nano

Internship in Machine Learning :

• Overview A.I | Machine Learning
• Introduction to Python | How to write code in Google Colab, Jupyter Notebook, Pycharm & IDLE

Supervised Learning – Classification & Regression

• Advertisement Sale prediction from an existing customer using LOGISTIC REGRESSION
• Salary Estimation using K-NEAREST NEIGHBOR
• Character Recognition using the SUPPORT VECTOR MACHINE
• Titanic Survival Prediction using NAIVE BAYES
• Leaf Detection using DECISION TREE
• Handwritten digit recognition using RANDOM FOREST
• Evaluating Classification Model Performance using CONFUSION MATRIX, CAP CURVE ANALYSIS & ACCURACY PARADOX
• Classification Model Selection for Breast Cancer Classification
• House Price Prediction using LINEAR REGRESSION Single Variable
• Exam Mark Prediction using LINEAR REGRESSION Multiple Variable
• Predicting the Previous salary of the New Employee using POLYNOMIAL REGRESSION
• Stock price prediction using SUPPORT VECTOR REGRESSION
• Height Prediction from the Age using DECISION TREE REGRESSION
• Car price prediction using RANDOM FOREST
• Evaluating Regression model performance using R-SQUARED

Intuition & Adjusted R-Squared Intuition 

• Regression Model Selection for Engine Energy Prediction.

Unsupervised Learning – Clustering

• Identifying the Pattern of the Customer Spent using K-MEANS CLUSTERING
• Customer Spending analysis using HIERARCHICAL CLUSTERING
• Leaf types data visualization using PRINCIPLE COMPONENT ANALYSIS
• Finding Similar Movie based on ranking using SINGULAR VALUE DECOMPOSITION

Unsupervised Learning – Association

• Market Basket Analysis using APIRIORI
• Market Basket Optimization/Analysis using ECLAT

Reinforcement Learning

• Web Ads. Click through Rate optimization using UPPER BOUND CONFIDENCE

Natural Language Processing

• Sentimental Analysis using Natural Language Processing
• Breast cancer Tumor prediction using XGBOOST

Deep Learning

• Bank Customer classification using ANN
• Pima-Indians Diabetes Classification using CONVOLUTIONAL NEURAL NETWORK
• A.I Snake Game using REINFORCEMENT LEARNING

Internship in Data Analytics :

• Introduction to Artificial Intelligence, Data Analytics & Road Map to Become a Data Scientist

Excel

• Data Preparation – Power Query & Tables
• Data analytics- Formula & Pivot Table
• Story Telling – Charts & Dashboard
• Automation – VBA Macros & Power Query

Statistics & Probability

• Descriptive Statistics – Mean, Mode, Median, Quartile, Range, InterQuartile Range, Standard Deviation
• Probability – Permutations, Combinations
• Population and Sampling
• Probability Distributions – Normal, Binomial and Poisson Distributions
• Hypothesis Testing & ANOVA – One Sample and Two Samples – z Test, t-Test, F Test and Chi-Square Test

BI tools – Tableau

• Connect Tableau to a Variety of Datasets
• Analyze, Blend, Join, and Calculate Data
• Visualize Data in the Form of Various Charts, Plots, and Maps

BI tools – Power BI

• Connect Tableau to a Variety of Datasets
• Visualize Data in the Form of Various Charts, Plots, and Maps and Calculate Data

Python

• Introduction to Python & Installing Python and its Libraries
• Basic Python Programming for Data Analytics

Numpy & Pandas

• Python Numpy functions
• Pandas for Data Analytics in Python

Data Visualization

• Matplotlib for data visualization
• Seaborn for data visualization

Kaggle Exploratory

• Kaggle Dataset and Notebooks

Database – SQL

• SQL Basics for Data Analytics – Part-1
• SQL Basics for Data Analytics – Part-2

Database – MongoDB

• MongoDB Basics for Data Analytics

Machine Learning

• Introduction to Machine Learning & its Libraries
• Evaluating and Deploying Machine Learning Classification algorithm for the classification of the State of the Electric power system

Deep Learning

• Introduction to Deep Learning & its Libraries
• Covid-19 Detection Using X-Ray Images with CNN

Natural Language Processing

• Tag Identification system using NLTK

What you will get

✅ Complete Video recordings of the course

✅ All attachment Download – PPT,

✅ Private Community Access

✅ E-Internship Certificate

✅ Lifetime course validity

Sample Internship Certificate

Frequently asked questions

1. Once I have Done the Payment where should I access the course?
   After the payment is done. Please signup to learn.pantechsolutions.net using the same mail id used for payment.
2. Where can I access the course?
   You can access the courses in our learning portal learn.pantechsolutions.net
3. What is the validity of the course?
   Each course’s validity varies from each plan you have chosen.
4. Is it only Self Paced Learning or I will get a Live session?
   It is a Self-paced Learning. Apart from that you will be having live sessions on Mastermind
5. Where can I clear my doubts?
   You can clear doubts in Weekly Mastermind Session.
6. Will you provide job opportunities?
   We will provide all the skillset that is needed to get a job
7. Can I Take More than One Course at a Time?
   Yes, you can each progress of the course will be noted respectively.
8. My Payment Did Not Go Through. What Do I Do?
   Please Mail us to learn@warriorsway.in
9. When do I get my internship Certificate?
   The internship Certificate will be generated automatically in the portal after completing the course for 100% . you can download from the portal for the respective course.

For an Internship on Python: Click here