Machine Learning with Python

Machine Learning is a method of data analysis that automates analytical model building. Machine Learning with Python course introduces the fundamental concepts and techniques of Machine Learning using a popular computer programming language, Python, that is used to develop websites, build software, and automate tasks.

ELIGIBILITY: This course is best suited for graduates who intend to pursue a career in Data Science or Data Analytics also with an aim to develop knowledge of Python Language. Anyone interested to apply for Machine Learning with Python course must have:

• Basic programming knowledge
• Familiarity with statistics

CAREER OPPORTUNITIES:

Market Trends: Machine Learning has emerged to be the most in – demand technical skill globally in recent years. The annual growth rate of Machine Learning jobs is estimated to be over 40% during the next six years, which represents a market value of almost $31 billion by 2024. Machine Learning job trends are set to impact every industry, creating demand for experts in this field, hence the valuable knowledge of Python combined with Machine Learning provides an extra edge to the professionals.

Salary Trends: Machine Learning jobs are a great choice for a high – paying career that will remain in demand for decades to come. In Dubai, United Arab Emirates (UAE), the median gross salary for a Machine Learning Engineer is AED 315,790 annually, ranking as one of the highest paying jobs in the UAE.

Demand and Opportunities: Machine Learning has proliferated, with expertise in this field ranking as the most in – demand technical skill. In a recent report by Research and Markets, the global Machine Learning market is predicted to grow from $1.4 billion in 2017 to $8.8 billion by 2022. These statistics are evidence of the potential growth of AI and Machine Learning jobs in the global job market.

COURSE OUTLINE:

Python for Machine Learning

• Programming Basics
• Python Data Types
• Structures and conditional statements
• Python core packages
• Introduction to Jupyter Notebook
• Introduction to Numpy and Pandas
• Data filtering and selecting
• Find duplicates and treating missing values
• Concatenate and transform data

Introduction to Machine Learning

• Overview of Supervised and Unsupervised Machine Learning
• Linear Regression
• Clustering with K – means
• Naive Bayes Classification
• Introduction to Neural Networks

Machine Learning Algorithm

• Supervised Machine Learning algorithms
• K – Nearest Neighbors (KNN) concept and application
• Naive Bayes concept and application
• Logistic Regression concept and application
• Classification Trees concept and application
• Unsupervised Machine Learning algorithms
• Clustering with K – means concept and application
• Hierarchical Clustering concept and application

Basic Statistics for Machine Learning

• Basic Statistics and Exploratory Analysis
• Descriptive summary statistics with Numpy
• Summarize continuous and categorical data
• Outlier analysis

Data Processing for Machine Learning

• Advanced – Data Mugging
• Outlier Analysis
• Treating for missing values
• Normalization vs Standardization of data

Building and Learning Machine Learning Model

• Setting up the project with ML workflow.
• Data Preprocessing and statistical exploration
• Building, Training, and evaluation of Machine Learning Model

Hand on Case Study: Property Estimation with ML

• Analysis of the case study: Property Estimations
• Setting up the project with ML workflow
• Data Preprocessing and statistical exploration
• Choosing the Machine Learning Algorithm for this case
• Building, Training, and evaluation of Machine Learning Model

KEY TAKEAWAYS:

After completing the Machine Learning with Python course, participants will be able to:

• Understand the principles and applications of Machine Learning
• Explore the utilization of Machine Learning through Python
• Analyze, manipulate, and visualize data using Python libraries
• Design Machine Learning algorithm
• Comprehend and analyze data structures and intricate logic
• Optimize predictive performance with multiple learning algorithms

ACCREDITATION:

Our Machine Learning with Python course is accredited by ISO 9001: 2015 and the Knowledge and Human Development Authority (KHDA).

ALUMNI: Our academy graduates are successfully placed in some of the top – notch companies in Dubai like Jumeirah, Aramex, Airarabia, Damac, Emaar, etc. They are entrepreneurs, career changers, and lifelong learners.

WHY LEARNER’S POINT:

As one of the top providers of Machine Learning with Python courses, we have extensive experience and comprehensive knowledge in the field.

The following are the key benefits offered by our Machine Learning with Python course:

• Our Machine Learning with Python course is designed based on real – world scenarios, formulating and evaluating practical requirements
• Our courses strive to provide a reality check and insight into the requirements of a challenging role and how to fulfill it
• We also provide live interactive sessions and hands – on experience through assignments associated with the actual work environment
• To enhance the learning experience of our students we provide organized group sessions and integrated training modules
• Our discrete approach to career guidance enables our students to get successfully placed in renowned organizations