Data Analytics and Machine Learning with Phyton

Tujuan Program

Practical Knowledge to Create and Contribute to to Machine Learning

Techniques to Create and Contribute to to Machine Learning

Python and the Anaconda Package Management System

Different Types of Data Science Problems

Loading the Case Study Data with Jupyter and Pandas

Activity-1: Importing and Overviewing Data

Who Needs This?

Fresh Graduate

IT Developer

Full Stack Developer

Supervisor IT

Data Scientist

What You Learn?

◾ Data Exploration and Cleaning
◾ Dealing with Missing Values
◾ Data Formatting in Python
◾ Data Normalization in Python
◾ Turning Categorical into Quantitative variables
◾ Activity-2: Data Cleaning and Exploring Data

◾ Introduction to Machine Learning
◾ Supervised and Unsupervised
◾ Python for Machine Learning
◾ Model Performance Metrics
◾ Activity 3: Performing Basic Machine Learning Algorithm using Python

◾ Introduction to Regression
◾ Plotting Regression
◾ Simple and Multiple Linear Regression
◾ Overfitting and Underfitting
◾ Polynomial Regression
◾ Activity 4: Implementing a Regression Model

◾ Introduction to Classification
◾ K-Nearest Neighbours
◾ Evaluation Metrics
◾ Logistic Regression
◾ Logistic vs Linear Regression
◾ Decision Trees
◾ Activity 5: Implementing a Classification Model

◾ Introduction to Clustering
◾ K-Means Clustering
◾ DBSCAN and Hierarchical Clustering
◾ Activity 6: Implementing a Clustering Model

Berapa Nilai Investasi
Yang Diperlukan?

IDR 10.500.000/pax