Data Science With Python - Classroom

This course will guide you in learning how to utilize the strength of Python in data analysis, creating appealing visualizations, and using robust machine learning algorithms. This course is designed for both beginners with basic programming experience and experienced developers who are willing to jump into Data Science.

Data Scientist is one of the most amazing career options that offer high salaries, immense job satisfaction, and astonishing growth opportunities. Further, this profession offers an amazing job satisfaction rating of 4.4 out of 5. As per the survey by Harvard Business Review, Data Scientist is the most desirable profession of the 21st century. In this course, we will work on your core skills like a python programming language, frameworks for data science processes, Machine learning, and data science projects, hands-on practice of data preprocessing techniques, and a lot more.

Career perspective

Data science is one of the most lucrative and desirable career options for It Professionals. As per the survey growth for data science, jobs will grow about 30% through 2026. Currently, the average salary of a Data Scientist in the UK is £49,591 annually. Data scientists are hot assets currently. A career in this domain promises insanely high salary, Global recognition, and amazing growth opportunities.

Data science is everywhere, be it smart cars, automated voice assistants, smart factories, smart sales predictions, smart investment, smart marketing, and advertising, smart decision making, and many more. Companies across the globe are rushing towards automation which manifests that there is a huge demand for data science professionals. Top companies like Facebook, Apple, Google, Oracle, Microsoft, IBM, Amazon, and many more hiring data science professionals.

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.

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

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.

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 (Optional Add-on Programs)

Job Guarantee is an add-on program you can register with this course. You will need to clear an assessment interview to get enrolled. Once successful in the assessment, you will be offered Job Guarantee with this certificate course. There is a fee to join this program as it takes you to rigorous career development, interview preparation, mock interviews, etc. The fee for joining the Job Guarantee add-on program is £500. This is a 12 months program which starts at the end of your certificate course. As part of this program, we represent you to the prospective employers and train on career development elements You need to abide by the rules of this program which you can find on the Job Guarantee page. If we can’t find you a relevant job or you don’t find it by yourself in the similar industry in any part of the world within these 12 months, we will refund you the course fee + Job Guarantee program fee. The refund process will start after the end of the 12 months and every month we will pay £500 until the entire fee is paid back. But if you find a relevant job during this time then the remaining payments will be stopped. This program is only applicable to home students (UK permanent residents / citizens).

Prerequisites have been met

Option 1

1. Topic: Data Science with Python (Prior Knowledge of Python Required)
2. Add-On:
3. Duration: 3 Months

Option 2

1. Topic: Data Science with Python (Prior Knowledge of Python Required)
2. Add-On:Project
3. Duration: 5 Months

Option 3

1. Topic: Data Science with Python (Prior Knowledge of Python Required)
2. Add-On: Project &Industrial Training and Paid Internship Program
3. Duration: 12 Months

Prerequisites have not been met

Option 1

1. Topic: Python + Data Science with Python
2. Duration: 4 Months

Option 2

1. Topic: Python + Data Science with Python
2. Add-On:Project
3. Duration: 6 Months

Option 3

1. Topic: Python + Data Science with Python
2. Add-On: Project &Industrial Training and Paid Internship Program
3. 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.

Course Highlights

• Hands-on practice

• Industry-standard Project development

• Learn from experts

• Interactive teaching

• Personality development

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 Data science

• Amazing job opportunities as the demand for data science professionals is increasing at a high pace

• As per the survey average salary of data science, professionals is £52,052.

• Data science enhances your decision-making power and it is easy to learn and understand.

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

About the Course

This course will guide you in learning how to utilize the strength of Python in data analysis, creating appealing visualizations, and using robust machine learning algorithms. This course is designed for both beginners with basic programming experience and experienced developers who are willing to jump into Data Science.

You will learn how to use NumPy, Seaborn, Pandas, Matplotlib, Python overview, Machine Learning concepts, and more. Further, you will get a chance to enhance your learning skills through Hands-on experience and live project development.

• This course enhances your data science skills to help you land your dream job.

• Through this course, you will get in-depth information about python and its data science 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 different data sciences techniques like NumPy, Pandas, Seaborn, and Matplotlib.

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

Who should apply for this course?

• Students who are willing to take data science as a career and want proficiency in this 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 data science.

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

Learning Objectives

• Use Python for Data Science and Machine Learning

• Use Spark for Big Data Analysis

• Implement Machine Learning Algorithms

• Learn to use NumPy for Numerical Data

• Learn to use Pandas for Data Analysis

• Learn to use Matplotlib for Python Plotting

• Learn to use Seaborn for statistical plots

• Use Plotly for interactive dynamic visualizations

• Use SciKit-Learn for Machine Learning Tasks

• K-Means Clustering

• Logistic Regression

• Linear Regression

• Random Forest and Decision Trees

• Natural Language Processing and Spam Filters

• Neural Networks

• Support Vector Machines

1. Some prior programming experience
2. Basic Understanding of English
3. Basic knowledge of computer
4. Ability to work in a team

Data Analyst

Data Engineers

Database Administrator

Machine Learning Engineer

Data Scientist

Data Architect

Certificate of completion

Digital certificate - Included