Machine Learning with Python (Classroom)

Machine Learning has become a vast field in computer science. It is basically getting things done by the computers without explicitly programming them. It has given us so many technologies self-driving car, speech recognition, web recommendation engines, etc.

Machine Learning, refers to a process of analysing data for training or building models. It is everywhere; from Amazon product recommendations to self-driven cars, it has great value throughout. As per the latest survey, the machine learning market is expected to grow by 43% by 2024. This revolution has greatly enhanced the demand for machine learning professionals.

Machine learning jobs have had a significant growth rate of 75% in the last four years, and the industry is rapidly continuously. In this course, we will work on your core skills like Machine Learning, and Learn specific topics like NLP, Reinforcement Learning, Deep Learning, and a lot more.

Career Perspective

Machine Learning is a process of analyzing data for training and building models. ML is just everywhere; from self-driven cars to Amazon product recommendations, it holds great value throughout. As per the latest survey, the global machine learning market is expected to grow by 43% by the year 2024. This revolution has increased the demand for machine learning professionals to a huge extent.

Machine learning and Artificial Intelligence jobs have had a significant growth rate of 75% in the last four years, and the industry is growing rapidly. The average salary of an ML professional is £52,000. A career in the Machine learning domain offers excellent growth, job satisfaction, insanely high salary, but it is a complex and challenging process.

Technologies Covered

• Python programming language: It is an interpreted high-level programming language used for web development, machine learning, AI, ML, and a lot more. It provides a clear approach to programmers to write a clear and logical approach.

• Pandas is a software library used for Data Analysis and manipulation. It offers operations and data structure and operations for manipulating time series and numerical tables.

• NumPy: it is a python library that consists of the multidimensional array and a collection of mathematical functions to operate on this array

• Matplotlib is a python library that makes matplotlib work like MATLAB. It provides an object-oriented API for inculcating plots into the application using GUI.

• Plotly is an open-source plotting library that supports a wide range of scientific, financial, and geographical use cases.

• SciKit-Learn is a Machine Learning library for the Python programming language. It features various regression, classification, and clustering algorithms.

Job Guarantee Program

The Job Guarantee program is available only to candidates who enrol in Option 3 (Project and Industrial Training and Paid Internship Program). It is important to note, however, that the Job Guarantee program has its own selection criteria, so not everyone may be considered for the program. 

Prerequisites have been met

Option 1

• Topic: Machine Learning (Prior Knowledge of Python Required)

• Add-On:

• Duration: 3 Months

Option 2

• Topic: Machine Learning (Prior Knowledge of Python Required)

• Add-On:Project

• Duration: 5 Months

Option 3

• Topic: Machine Learning (Prior Knowledge of Python Required)

• Add-On: Project &Industrial Training and Paid Internship Program

• Duration: 12 Months

Prerequisites have not been met

Option 1

• Topic: Python + Machine Learning

• Duration: 4 Months

Option 2

• Topic: Python + Machine Learning

• Add-On:Project

• Duration: 6 Months

Option 3

• Topic: Python + Machine Learning

• Add-On: Project &Industrial Training and Paid Internship Program

• Duration: 13 Months

Note: Our Industrial Training and Internship program includes a guaranteed 6 months paid internship (from 10 hours to 40 hours per week) with a technology company. Due to visa restrictions, some international students may not be able to participate in this program.

Who should apply for this course?

• Students who are willing to take machine learning as a career and want proficiency in this domain.

• It is also a great course for working professionals who want to shift to the Machine learning domain.

• Students who want to achieve a great and successful career.

• It is the best course for students who want to build a strong foundation in Machine learning.

Evaluation Criteria

• Anyone interested in Machine Learning.

• College students who want to build a career in Data Science.

• Data analysts who are willing to level up in Machine Learning.

• People who are dissatisfied with their job and are willing to become Data scientists.

• People who are willing to add value to their business by using robust Machine Learning tools.

• Students must have at least high school knowledge in maths and must be willing to learn Machine Learning.

• Any intermediate-level person who has an idea about the basics of machine learning, classical algorithms like logistic regression or linear regression, but who wants to learn more about it and explore different fields of Machine Learning.

Course Highlights

• Hands-on practice

• Industry-standard Project development

• Learn from experts

• Interactive teaching

• Full lifetime access

• Access on mobile

• Certificate of completion

Evaluation Criteria

• 18 Coding exercises

• 5 Assignments

• 5 Quizzes

• Capstone Project

• Group activities

• Presentations

Assessment Criteria

To earn the certificate, students must clear all the assessments, quizzes, and project work. At a minimum, students are required to satisfy the pass criteria of the course. Students who score 75% or more will be awarded Merit Grade, while students with 85% or more will be awarded, Distinction Grade.

Following are the detailed criteria for each level

Pass Grade Criteria

Score minimum 50% aggregate and demonstrate the following;

• Proficiency in the technical skills and techniques

• Must have a minimum attendance of 90% in the classes unless proper medical proof is provided

• Submit all the projects and assignments before the last submission date

• Collaborate with peers in group projects

Merit Grade Criteria

Score minimum 75% aggregate and demonstrate the following;

• Excellent technical skills and techniques

• Discover and apply strategies to find the perfect solutions

• Select/design and apply appropriate methods/techniques

• Present and communicate appropriate findings

Distinction Grade Criteria

Score minimum 85% aggregate and demonstrate the following;

• Mastery of technical skills and techniques

• Use critical thinking for self-evaluation and justify valid conclusions

• Take the responsibility the manage and organise activities and teams

• Showcase convergent/lateral/creative thinking.

Reasons to learn Machine learning

• Amazing job opportunities as the demand for Machine learning professionals is increasing at a high pace

• Machine learning enhances your decision-making power and it is easy to understand and learn.

• As per the survey average salary of machine learning, professionals is £52,000.

• Less completion in the field as there is an alarming gap between the demand and supply of machine learning professionals.

About Course

If you are willing to build your career in Machine Learning. Then this course is exclusively for you!

This course will help you learn about complex theory, algorithms, and coding libraries in a much simpler way. We will be your guide and help you ace into the World of Machine Learning.

With every tutorial, you will learn new skills and improve your understanding of this lucrative sub-field of Data Science. This course is exciting and challenging, but at the same time, we dive deep into the concepts of Machine Learning.

• This course enhances your machine learning skills to help you land your dream job.

• Through this course, you will get in-depth information about python and its machine learning library.

• Career guidance and doubt resolving sessions with industry experts.

• Learning through hands-on experience and live project development.

• You will learn in detail about NLP, Reinforcement Learning, and Deep Learning, and a lot more.

Reasons to Choose LSET

• Interactive live sessions by industry experts.

• Practical classes with project-based learning with hands-on activities.

• International learning platform to promote collaboration and teamwork.

• Most up-to-date course curriculum based on current industry demand.

• Gain access to various e-learning resources.

• One-to-one attention to ensure maximum participation in the classes.

• Lifetime career guidance to get the students employed in good companies.

• Free lifetime membership to the LSET Alumni Club

Complete Learning Experience

This course provides a hands-on, guided learning experience to help you learn the fundamentals practically.

• We constantly update the curriculum to include the latest releases and features.

• We focus on teaching the industry's best practices and standards.

• We let you explore the topics through guided hands-on sessions.

• We provide industry professional mentor support to every student.

• We give you an opportunity to work on real world examples.

• Work with hands-on projects and assignments.

• We help you build a technical portfolio that you can present to prospective employers.

What Will Be Your Responsibilities?

• Work creatively in a problem-solving environment.

• Ask questions and participate in class discussions.

• Work on assignments and quizzes promptly.

• Read additional resources on the course topics and ask questions in class.

• Actively participate in team projects and presentations.

• Work with the career development department to prepare for interviews

• Respond promptly to the instructors, student service officers, career development officers, etc.

• And most importantly, have fun while learning at LSET.

Benefits of LSET Certificate

Earning the LSET Certificate means you have demonstrated hard-working capabilities and learnt the latest technologies by completing hands-on exercises and real-world projects.

Following are some of the traits employers can trust you have built up through your course;

• You know how to work in a team environment and communicate well.

• You know the tools which are necessary for your desired job.

• You know how to use the latest technologies to develop technologically advanced solutions.

• You have developed problem-solving skills to navigate complex problem scenarios and find the right solutions.

• You are now ready to take on the challenge and help your prospective employer to build the desired solutions.

What to expect after completing the course?

After earning your certificate from LSET, you are entitled to join the LSET’s Alumni club. There are countless benefits associated with the Alumni Club membership. As a member of LSET Alumni you can expect the following;

• LSET to hold your hand all the way to find a successful career

• Advice you on choosing right career based on your passion and goals

• Connect you with industry experts for career progression

• Provide you opportunities to participate in events to keep yourself updated

• Provide you an opportunity to contribute to the game changing open source projects

• Provide you a platform to shine by giving you an opportunity to speak at our events

How Does Project-Based Learning Work?

LSET project-based learning model gives students an opportunity to work on the real-world applications and apply their knowledge and skills gained in the course to build high performing industry grade applications.

As part of this course, students learn agile project management concepts, tools, and techniques to work on the assigned project in collaborative manner. Project work is done individually by each student but they are encouraged to enhance their solution by collaborating with the teammates.

Requirements

• Students must have at least high school knowledge in maths and must be willing to learn Machine Learning.

• Basic Understanding of English

• Basic Proficiency with Computers

• Ability to work in Group

Career path

• Machine Learning Engineer

• Business Intelligence (BI) Developer

• Data Scientist

• Human-Centered Machine Learning Designer

• Computational Linguist

• Software Developer