Certificate Course in
Data Science using Python and R Programming
- 48 Hours Classroom & Online Sessions
- 80 Hours Assignments & Real-Time Projects
3152 Learners
Academic Partners & International Accreditations
"The global focus has shifted towards the field of data science and the average salary for a Data Scientist is $123735 per year in the United States." (Source - Glassdoor). The big story of the past decade is the explosion of data – a.k.a., ‘big data’ and how that is disrupting enterprises across all domains. As we step into the new decade, enterprises are focusing more on becoming data-driven by leveraging Data Analytics tools and techniques. With such a focus on advanced analytics capabilities, companies are searching for individuals who possess these skills to help in their vision. The Data Analytics training by 360DigiTMG is an effort to reduce this skill gap. In the USA, the big-data adoption of enterprises shot up by 59% in 2018 alone and this trend is poised to continue in 2020 and beyond. Participants of this training can aim to get employment in some of the hottest job markets in the USA – including Silicon Valley. The USA is the home of innovation with some of the best and bright minds living here. There are a lot of start-ups and research centres in this country which craves and embraces innovation. In addition to being a technologically advanced nation, it is also a potpourri of varied cultures and cuisines. That makes this country a truly unique place in the world, with cuisines from across the world.
Data Science
Total Duration
3 Months
Prerequisites
- Computer Skills
- Basic Programming Knowledge
- Analytical Mindset
Data Science Training Overview
Leapfrog your career in Analytics with "Data Analytics using Python and R programming" course. Gain hands-on experience in performing Exploratory Data Analysis and Data Mining using Python and R. Learn how Machine Learning algorithms can help extract useful business insights and achieve data-driven decision-making. The Certification Program in Data Analytics using Python and R provides a detailed introduction on how to use Python and R to programmatically interrogate structured (RDBMS) and unstructured (Big Data) data. Understand the different types of machine learning techniques like supervised and unsupervised learning. Get introduced to techniques like Neural Networks, SVM and present your findings with attractive Data Visualization techniques.
What is Data Science?
Data Science encompasses a wide variety of roles and tasks including collecting data, analytics, extracting knowledge and insights, identifying and predicting trends, plotting, machine learning, or artificial intelligence. Data is the foundation of Data Science and we have been generating data at an unprecedented rate through texts, numbers, audio, images, mobiles, social media, etc. All this data needs to be segregated into the relevant, structured and well-organized format. A Data Scientist is a specialist who deals with raw data and designs ways to retrieve process and consume this data with the intent to measure performance and predict future behaviour.
Data Science Course Learning Outcomes
The aim of this course is to help students learn, understand, and explore analytics and machine learning approaches. Billions of devices are connected to the internet today and are generating around 32 million terabytes of data every day. Data science is a field that helps uncover vital data and sets it on track by slicing out meaningful information and other prime aspects crucial to any business operations. In this course, students will learn to handle numerical information, visualize the findings and create images to understand the insights from the data and make predictions or informed decisions. They will explore all fundamentals and various methods within data science which includes data processing, data extraction, statistics, descriptive and predictive analytics and machine learning approaches using Python and R. They will also analyze and relate to various data generation sources and evaluate different storage and data processing technologies. This training also contributes to enhancing the communications skills of students who will be presenting and communicating their findings of comprehensive data analysis using Data Visualization for easy understanding and communication. The goal of this training in the USA is to equip students with the in-demand data science skills of data extraction, wrangling and pre-processing to derive conclusions from the data. Students will also learn to
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Who Should Sign Up?
- IT Engineers
- Data and Analytics Manager
- Business Analysts
- Data Engineers
- Banking and Finance Analysts
- Marketing Managers
- Supply Chain Professionals
- HR Managers
- Math, Science and Commerce Graduates
Data Science Training Modules
These modules provide students with the essential skills needed to comprehend the language of data and solve data problems across various sectors and industries using Python and R. The modules aim to deliver knowledge relating the conceptualization and summarization of data, representation of data, data computing technologies, and handling data science projects. Students are first introduced to various techniques like Data Preparation, Data cleansing, Hypothesis Testing, Regression, Machine Learning Algorithms, Neural Networks, etc. By the end of the course, students will be able to build models using Python and R and gain expertise in object-oriented programming using Python. These learning will give the students ability to scale up machine learning techniques and technologies.
- Python:
- Python and Flask based local deployment - Build, train and deploy an ML model using Python and Flask: This module is a completely hands on, where you will train a model and deploy it to a web app using Flask framework.
- AWS SageMaker based cloud deployment - Cloud based deployment: Build, train and deploy ML model using AWS SageMaker
- R: Deploy a web app using RStudio and RShiny app
Tools Covered
Data Science Trends in USA
Data has always narrated the story of our lives and has evolved and boomed in recent years. We are experiencing an explosion of data from airline, mining and auto industries. This pace at which data is being generated is not expected to slow down in the coming years especially with IoT devices connected via the internet and are delivering richer and more diverse data types. Today, more and more platforms use data science and have created a dire need for Data Scientists across various industries for their digital transformation journeys. The upcoming trends in this field will include further advancement in Artificial Intelligence, privacy and security of data, cloud welcoming data, and blockchain technology.
Python will see an increase in its demand by Data Scientists who will use it for their research and algorithms. Cloud serving vendors like Google and Amazon will have to provide more storage space for global organizations and banks to store the huge amount of data generated by them. Another trend will be the concern for the security of the data and we will see a lot of progress around ensuring privacy and security of information. AI will also be seen to push rapidly into industrial scenarios. With so many trends that are set to shape the digital environment, the future of data Science is indeed going to be very exciting and innovative. The course in Data Science using Python and R in the USA will give you an opportunity to be part of the data revolution.
How We Prepare You
- Additional Assignments of over 80 hours
- Live Free Webinars
- Resume and LinkedIn Review Sessions
- 3 Month Access to LMS
- 24/7 support
- Job Assistance in Data Science Fields
- Complimentary Courses
- Unlimited Mock Interview and Quiz Session
- Hands-on Experience in a Live Project
- Life Time Free access to Industry Webinars
Call us Today!
Certificate
Earn a certificate and demonstrate your commitment to the profession. Use it to distinguish yourself in the job market, get recognised at the workplace and boost your confidence. The Data Science Certificate is your passport to an accelerated career path.
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Alumni Speak
"The training was organised properly, and our instructor was extremely conceptually sound. I enjoyed the interview preparation, and 360DigiTMG is to credit for my successful placement.”
Pavan Satya
Senior Software Engineer
"Although data sciences is a complex field, the course made it seem quite straightforward to me. This course's readings and tests were fantastic. This teacher was really beneficial. This university offers a wealth of information."
Chetan Reddy
Data Scientist
"The course's material and infrastructure are reliable. The majority of the time, they keep an eye on us. They actually assisted me in getting a job. I appreciated their help with placement. Excellent institution.”
Santosh Kumar
Business Intelligence Analyst
"Numerous advantages of the course. Thank you especially to my mentors. It feels wonderful to finally get to work.”
Kadar Nagole
Data Scientist
"Excellent team and a good atmosphere. They truly did lead the way for me right away. My mentors are wonderful. The training materials are top-notch.”
Gowtham R
Data Engineer
"The instructors improved the sessions' interactivity and communicated well. The course has been fantastic.”
Wan Muhamad Taufik
Associate Data Scientist
"The instructors went above and beyond to allay our fears. They assigned us an enormous amount of work, including one very difficult live project. great location for studying.”
Venu Panjarla
AVP Technology
Our Alumni Work At
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FAQs for Data Science Bootcamp
Different organisations use different terms for Data Professionals. You will sometimes find these terms being used interchangeably. Though there are no hard rules that distinguish one from another, you should get the role descriptions clarified before you join an organisation.
With growing demand, there is a scarcity of Data Science professionals in the market. If you can demonstrate strong knowledge of Data Science concepts and algorithms, then there is a good chance that you can carve a successful career in this domain.
360DigiTMG provides internship opportunities through Innodatatics, our USA-based consulting partner, for deserving participants to help them gain real-life experience. This greatly helps students to bridge the gap between theory and practice.
There are plenty of jobs available for Data Professionals. Once you complete the training, assignments and the live projects you can enroll for placement assistance. We help our students in resume preparation. Once the resume is ready we will float it organisations with whom we have formal agreements on job placements.
We also conduct webinars to help you with your resume and job interviews. We cover all aspects of post-training activities that are required to get a successful placement. After placement we provide technical assistance for the first project on the job.
After you have completed the classroom sessions, you will receive assignments through the online Learning Management System that you can access at your convenience. You will need to complete the assignments in order to obtain your Data Scientist certificate.
While there are a number of roles pertaining to Data Professionals, most of the responsibilities overlap. However, the following are some basic job descriptions for each of these roles.
As a Data Analyst, you will be dealing with Data Cleansing, Exploratory Data Analysis and Data Visualisation, among other functions. The functions pertain more to the use and analysis of historical data for understanding the current state.
As a Data Scientist, you will be building algorithms to solve business problems using statistical tools such as Python, R, SAS, STATA, Matlab, Minitab, KNIME, Weka etc. A Data Scientist also performs predictive modelling to facilitate proactive decision-making. Machine learning algorithms are used to build predictive models using Regression Analysis.A Data Scientist has to develop expertise in Neural Networks and Feature Engineering.
A Data Engineer primarily does programming using Spark, Python, R etc. It often complements the role of a Data Scientist.
A Data Architect has a much broader role that involves establishing the hardware and software infrastructure needed for an organisation to perform Data Analysis. They help in selecting the right Database, Servers, Network Architecture, GPUs, Cores, Memory, Hard disk etc.
In this blended programme, you will be attending 48 hours of classroom sessions over six days on campus in Kuala Lumpur, Malaysia. After completion, you will have access to the online Learning Management System for another three months for recorded videos and assignments. The total duration of assignments to be completed online is 40-60 hours. If you satisfactorily complete the attendance and assignments,
you will have the opportunity to work for a real world project through Innodatatics, USA.
If you miss a class, we will arrange for a recording of the session. You can then access it through the online Learning Management System - Ai SPRY.
We assign mentors to each student in this programme. Additionally, during the mentorship session, if the mentor feels that you require additional assistance, you may be referred to another mentor or trainer.
No. The cost of the certificate is included in the programme package.
Jobs in the Field of Data Science in USA
Learning Data Science will accelerate your career and give you a chance to work for different job titles like Data Analyst, Data Scientist, Data Engineer, Business Analyst, Quantitative Analyst, Machine Learning Engineer, etc.
Salaries for Data Science Professionals in USA
In the United States, the average salary for a Data Scientist is $131513 per year. A Data Scientist with an experience of 1 year gets $103,152 per year and someone with a work experience of 5-6 years can easily fetch a salary of $142,111 per year.
Projects in the field of Data Science
To all the inquisitive data explorers out there, projects are the fun way to put your skills to practice. One can do projects related to network intrusion detection, email spam filtering, sensor-based environment monitoring, face recognition, and handwritten character recognition.
Role of Open Source Tools in Data Science
The tools of data science perform various operations concerning statistics, data cleaning, data extracting, data manipulation, stream processing, making interactive visualizations and performing complex calculations etc.
Modes of Training for Data Science
The course in the USA is designed to suit the needs of students as well as working professionals. We at 360DigiTMG give our students the option of both classroom and online learning. We also support e-learning as part of our curriculum.
Industry Applications of Data Science
Data Science applications are used across a variety of industries including manufacturing, Finance, Banking, Education, Agriculture, Automobiles, Travel, Gaming, Healthcare, etc.
Companies That Trust Us
360DigiTMG offers customised corporate training programmes that suit the industry-specific needs of each company. Engage with us to design continuous learning programmes and skill development roadmaps for your employees. Together, let’s create a future-ready workforce that will enhance the competitiveness of your business.
Student Voices