AI Researcher, ML Engineer
Aspiring for a high paying and challenging career? Get a head-start into one of the most sought after field as a Data Scientist and uplift your CV with this course!
As the world entered the era of big data, the need for its storage also grew. It was the main challenge and concern for the enterprise industries until 2010. The main focus was on building
Therefore, it is very important to understand what Data Science is, and how can it add value to your business.
What you will Learn
- Data Analysis
- Data Visualisation and Insights
- Fundamental principles of Statistics and Data Modelling
- Machine Learning, Artificial Neural Networks and Deep Learning
- R, Python, SQL and Tableau
- Careers in Data Science
About the Course
Data scientist is one of the best suited professions to thrive, in this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace. However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist. The Solution Data science is a multidisciplinary field. It encompasses a wide range of topics. - Understanding of the data science field and the type of analysis carried out - Mathematics -Statistics - Python - Applying advanced statistical techniques in Python - Data Visualization - Machine Learning - Deep Learning Our focus is to teach topics that flow smoothly and complement each other. The course teaches you everything you need to know to become a data scientist at a fraction of the cost of traditional programs (not to mention the amount of time you will save). The Skills 1. Intro to Data and Data Science Big data, business intelligence, business analytics, machine learning and artificial intelligence. We know these buzzwords belong to the field of data science but what do they all mean? 2. Mathematics Learning the tools is the first step to doing data science. You must first see the big picture to then examine the parts in detail. We take a detailed look specifically at calculus and linear algebra as they are the subfields data science relies on. 3. Statistics You need to think like a scientist before you can become a scientist. Statistics trains your mind to frame problems as hypotheses and gives you techniques to test these hypotheses, just like a scientist. 4. Python Python is a relatively new programming language and, unlike R, it is a general-purpose programming language. You can do anything with it! Web applications, computer games and data science are among many of its capabilities. That’s why, in a short space of time, it has managed to disrupt many disciplines. Extremely powerful libraries have been developed to enable data manipulation, transformation, and visualisation. Where Python really shines however, is when it deals with machine and deep learning. 5. Tableau Data scientists don’t just need to deal with data and solve data driven problems. They also need to convince company executives of the right decisions to make. These executives may not be well versed in data science, so the data scientist must but be able to present and visualise the data’s story in a way they will understand. That’s where Tableau comes in – and we will help you become an expert storyteller using the leading visualisation software in business intelligence and data science. 6. Advanced Statistics Regressions, clustering, and factor analysis are all disciplines that were invented before machine learning. However, now these statistical methods are all performed through machine learning to provide predictions with unparalleled accuracy. This section will look at these techniques in detail. 7. Machine Learning The final part of the program and what every section has been leading up to is deep learning. Being able to employ machine and deep learning in their work is what often separates a data scientist from a data analyst. This section covers all common machine learning techniques and deep learning methods with TensorFlow. You will become a data scientist from scratch The course has 2 real-time projects - Mini and Major projects, on completion of which you will receive a Certificate. Each project has been designed to be of use for your industrial or final year projects in college and also for your placements or job interviews. With this course you'll get 24/7 support, so if you have any questions you can post them in the Q&A section and we'll respond to you immediately. Unlike other courses, this course doesn't just teach Data Science but also motivates the student and creates a sense of interest for the subject too.
About The Coach
An undergraduate student pursuing Computer Science and Engineering, Rohith is a Teaching Assistant for Data Science and Artificial Intelligence at SRM University. He is also an AI Researcher and Rohith’s technical interests lie in Artificial Intelligence and Machine Learning, which makes him enthusiastic about working on cutting edge technologies and projects on Internet of Things and Block chain technology.
My experience with Unschool has been superb and I learnt a lot from my courses. It was wonderfully taught from the basics. I hope to be a part of more courses at Unschool. Whenever I had a query or was confused, they come to your aid immediately. I wish to see Unschool impacting many more students.
Amity University, Jaipur
The content provided by Unshool is quite helpful because the video shows practically along with theoretical information. Also, it is self-paced which helps us complete the training at our own convenience. The topics covered are also quite helpful and tell us about the real-world applications of a particular subject.
Cummins College Of Engineering for Women