Learn Data Science With Python with LSET Industry Expert
This course will guide you in learning how to utilise the strength of Python in data analysis, creating appealing visualisations, 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.
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*Modules of our curriculum are subject to change. We update our curriculum based on the new releases of the libraries, frameworks, Software, etc. Students will be informed about the final curriculum in the course induction class.
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.
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.
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.
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*Modules of our curriculum are subject to change. We update our curriculum based on the new releases of the libraries, frameworks, Software, etc. Students will be informed about the final curriculum in the course induction class.
We love to answer questions, empower students, and motivate professionals. Feel free to fill out the form and clear up your doubts related to our Data Science with Python Course
This course will guide you in learning how to utilise the strength of Python in data analysis, creating appealing visualisations, 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.
Following are the steps involved in the LSET’s project-based learning;
Step 1: Project Idea Discussion
In this step, students get introduced to the problem and develop a strategy to build the solution.
Step 2: Build Product Backlog
This step requires students to enhance the existing starter product backlog available in the project. This helps students to think about real-life business requirements and formulate them in good user stories.
Step 3: Design Releases and Sprints
In this step, students define software releases and plan sprints for each release. Students must go through sprint planning individually and learn about story points and velocity.
Step 4: Unit and Integration Tests
In this step, students learn to write unit tests to ensure every application part works fine.
Step 5: Use CICD to Deploy
In this step, students learn to use CICD (Continuous Integration Continuous Delivery) pipeline to build their application as a docker image and deploy it to Kubernetes.
London has been a leading international financial centre since the 19th century. In recent years, London has seen many FinTech start-ups and significant innovations in the banking sector. This project aims to introduce students to the financial industry and technologies used to handle billions of daily transactions. As part of this project, students will learn the current technological advances and build up their knowledge to start a simple banking application. This application uses agile project management practices to build basic functionality. Students will be presented with user stories to create the initial project backlog. Students need to enhance this backlog by adding more relevant user stories and working on them.
LSET emphasises project-based learning as it allows the students to master the course content by going through near real-world work experience. LSET projects are carefully designed to teach the industry-required skills and mindset. It motivates the students on various essential aspects like learning to work in teams, improving communication with peers, taking the initiative to look for innovative solutions, enhancing problem-solving skills, understanding the end user requirements to build user-specific products, etc.
Capstone Projects build students’ confidence in handling projects and applying their newly learned skills to solve real-world problems. This allows the students to reflect upon their learning and find the opportunity to get the most out of the course. Learn more about Capstone Projects here.
Start Your Journey to becoming a Professional Data Scientist
LSET could provide the perfect headstart to start your career in Data Science with Python.
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