پرورش کارشناس علم داده و هوش مصنوعی

Step 1: Data Wrangling
Data Gathering
Data Accessing
Data Cleaning
Real Project1: Income Statement for Forecasting by Machine Learning & Fundamentally Analysis
Real Project2: Project of Twitter account

Step 2: Data Visualization
Data Exploration & Visualization
Analysis of Categorical Variables
Analysis of numerical Variables
Charting for Relation Between Categorical and Numerical Variables
Multivariate Exploration of Data
Real Project: Data on Cars used for Testing Fuel Economy

Step 3: Data Forecasting
Introduction to Machine Learning
Supervised Learning Algorithm Theory
Unsupervised Learning Algorithm Theory
KNN / Regression Models / Bays classifier / Decision Tree
K-Means / SVM
Introduction to Metrics for Analyzing any Forecasting
Real Project1: Forecasting Home Price using some Features Home
Real Project2: Forecasting the Color of Diamonds in real Database

Introduction to Data Analysis, Data Scientist and Machine Learning Engineer
What is the role of Data Analysis
Data Scientist pipeline completely
What are Machine Learning & Deep Learning

Data Structures, Expressions and Functions in Python
Python & Anaconda & Jupyter Notebook
List / Tuple / Dictionary / Set / String ….
Class / Object / Function
For Loop / While / If / If Else

Important Libraries for Data Scientist
Data Preprocessing : Pandas / OS / Shutil / Sklearn
Numerical Libraries for Matrix : Numpy / Tensorflow / Keras
Data Visualization : Matplotlib / Seaborn / Plotty
More than 20 Examples and Small Projects
Real Project1: Exploring Weather Trend using Python and Excel
Real Project2: Medical Appointment for Data Analysis

Statistics in Python for Data Analysis
Descriptive Statistics
Hypothesis Testing & Confidence Level
Regression Models
Logistic Regression
Analyze A/B Test
Real Project1: A/B test run by selecting the best stock
Real Project2: A/B test run by an e-commerce website

Deep Learning Process

Total processing of Deep Learning
Optimization Algorithms
Back Propagation Method
Kind of Loss Functions
Parameters / Hyper parameter / Learning Rate / Batch Size / Epoch
Regularization and Data Augmentation
Concept of Drop out
Activation Function

Convolution Neural Network

Concept of Deep Convolution Neural Network
Convolving Process
Kernel Matrix in CNN
Kind of Padding / Stride in CNN
MaxPooling
Resizing & Rescaling Matrix in Images
CV2 & CVtColor in Image Preprocessing
Image Classification and Coding in Python
Real Project1: Forecasting Class of Images on Mnist Database
Real Project2: Forecasting US index Dollar using Convolution 1D
Real Project3: Forecasting Classes in Cfar 10 using Convolution 2D

Recurrent Neural Network

Concept of RNN / LSTM / GRU
How does LSTM work
Data Preparation for Time Series
Normalization & Standardization
Modeling Using Stack LSTM
Convolution & LSTM for forecasting Time Series
Encoder – Decoder Networks
Real Project1: Forecasting Tehran Bourse Index using LSTM
Real Project2: Forecasting Irankhodro Stock Price using Encoder – Decoder & LSTM
Real Project3: Forecasting Income Statement using GRU / LSTM

Text Mining and Forecasting

What is NLP (Natural Language Processing)
Preprocessing on Text
Text Vectorization and Work Embedding
Modeling and Affective Forecasting
Real Project1: Forecasting of Affective in Comments

Classical Machine Learning

Introduction to Machine Learning
Classification vis Clustering
Supervised & Unsupervised Learning Theory
KNN / Regression Models / Logistic Regression / Bays classifier / K-Means
Decision Tree / Random Forest / XGboost / SVM / DRT
Introduction to Metrics for Analyzing any Forecasting
Real Project1: IRIS Project for Forecasting using Supervised Models
Real Project2: Weather Forecasting using Regression Models

Introduction to Machine Learning, Deep Learning and Artificial Intelligence

What is the different between Classical Machine Learning and Deep Learning
What is a Neural Network
Shallow Neural Networks via Hidden / Deep Neural Networks
Kind of Neural Networks
Concept of Feature Extraction in NN

Tools and Platforms for Deep Learning

Working with Google Colab
Anaconda & Pypi
Hardware / CPU & GPU & TPU
Introduction of Kaggle & GitHub

Introduction of Deep Learning Networks

Deep Feed Forward Neural Network
Deep Convolutional Neural Network
RNN / LSTM / GRU
Encoders / Decoders

Coding in Deep Learning

Data Preprocessing using Pandas and Numpy
Data Cleaning
Data Exploration for Feature Extraction
Data Normalization
Data Standardization
Tensorflow / Pytorch / Keras
Neural Networks and Non Neural Networks
How to train the model ( Data Training / Validation / Testing)
Forecasting (Classification & Regression)
Metrics & Evaluate Models
Real Project1: Forecasting the Color of Diamonds in real Database