What is Data Science?
What you'll learn
- You will gain a firm foothold of the fundamentals of Data Science.
- You will understand the important terminologies and statistical methods in data science
- You will understand the mathematics and statistics behind Machine Learning
- You will learn how to pre-process data
- Apply your skills to real-life business cases
- You will learn what percentile is with the help of examples
- Probability tells us how often some event will happen after many repeated trials, we start off with an introduction to this interesting topic.
- Learn the fundamental concepts of descriptive statistics
- You will learn how to collect data, how to visualize data, how to predict or explain different behaviors and events and how to find ideas for data research.
- No prior experience is required. We will start from the very basics
A Data Scientist dons many hats in his/her workplace. Not only are Data Scientists responsible for business analytics, they are also involved in building data products and software platforms, along with developing visualizations and machine learning algorithms
Data Analytics career prospects depend not only on how good are you with programming —equally important is the ability to influence companies to take action. As you work for an organization, you will improve your communication skills.
A Data Analyst interprets data and turns it into information which can offer ways to improve a business, thus affecting business decisions. Data Analysts gather information from various sources and interpret patterns and trends – as such a Data Analyst job description should highlight the analytical nature of the role.
Key skills for a data analyst
A high level of mathematical ability.
Programming languages, such as SQL, Oracle, and Python.
The ability to analyze, model, and interpret data.
A methodical and logical approach.
The ability to plan work and meet deadlines.
Accuracy and attention to detail.
What will I learn in this course:
You will gain a firm foothold on the fundamentals of Data Science.
You will understand the important terminologies and statistical methods in data science
You will understand the mathematics and statistics behind Machine Learning
You will learn how to pre-process data
You will learn what percentile is with the help of examples
You will learn the fundamental concepts of descriptive statistics
You will learn how to collect data, how to visualize data, how to predict or explain different behaviors and events and how to find ideas for data research.
It was a very good match ~ KEHINDE ADENIYE
yes,its a good match for me as I have my masters in Statistics. ~ Fancy Arora
The course is good and I would highly recommend this purely for beginners who do not have any idea of these concepts and the instructor was so good in making concepts more simple. ~ Sivathmika Vinnakota
This instructor is amazing......he has experience, he has knowledge, he understands the problems we gonna face while learning and solves them perfectly although he could have used some voice filters and subtitles because sometimes it's hard to understand he's saying but overall he is a masterclass instructor. ~ Tanjeel Ahmed
The facilitator did everything to simplify the course. ~ Prince Uwadiae
the course is quite insightful ~ Lydia Namsi
Who this course is for:
- The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
We specialize in Cybersecurity, Data Science and Talent Management/Human capital management training. The USP of all our training's is the hands-on that we provide, our focus is on real-life practical knowledge sharing, and not tool-based PPT slides. All our training's are conducted by highly experienced practitioners who are dyed-in-the-wool penetration testers. The material is cutting edge and updated with even the most recent developments. We have a standard set of courses outlined in different information security domains, data analytics domains and Talent management domain. However, we also customize the training according to the clients’ requirements.