Data Scientist Career Path

Uplatz provides this powerful and extensive Career Path program to help you become a Data Scientist. It is a program covering all topics related to Data Science and Machine Learning in the form of self-paced video tutorials. You will be awarded Course Completion Certificate at the end of the course.

Data Scientists are a new breed of analytical data experts who have the technical skills to solve complex problems. The data scientist role also has academic origins. The Data scientist’s toolbox terms and technologies are commonly used by Data Scientist, Data visualization, Machine learning, Deep learning, Data preparation, Text analytics. Most Data Scientists have backgrounds as data analysts or statisticians, other come from non-technical fields such as business or economics.

In today’s technologically advanced world the field is gaining immense popularity across different sectors. As a result of large chunks of data created in every nook and corner.

The following courses are covered in the Data Scientist Career Track program:

1. Data Science with Python
2. Data Science with R
3. Python Programming (basic to advanced)
4. R Programming for Beginners
5. R Programming
6. Machine Learning (basic to advanced)
7. Machine Learning with Python
8. Deep Learning Foundation
9. Deep Learning with Keras
10. Deep Learning with TensorFlow

The candidate must have Data Science skills:

Fundamentals of Data Science - The first and foremost important skill you require is to understand the fundamentals of data science, machine learning, and artificial intelligence as a whole. Difference between machine learning and deep learning, common tools, and terminologies.

Programming knowledge - Python is a general-purpose programming language having multiple data science libraries along with rapid prototyping whereas R is a language for statistical analysis and visualization.

Data Manipulation and Analysis – Data wrangling make take up a lot of time but ultimately helps you in taking better data-driven decisions. Some of the data manipulation and wrangling generally applied is – missing value imputation, correcting data types, and transformation.

The courses covered in Career Path - Data Scientist are:

1. Data Science with Python- Data is the new Oil. This statement shows how every modern IT system is driven by capturing, storing, and analyzing data for various needs. Be it about making decisions for the business, forecasting weather, studying protein structures in biology, or designing a marketing campaign.
2. Python Programming (Basic to advanced) is a General Purpose object-oriented programming language, which means that it can model real-world entities. It is also dynamically-typed because it carries out type-checking at runtime. It does so to make sure that the type of construct matches what we expect it to be.
3. R Programming - R is a programming language and software environment for statistical analysis, graphics representation, and reporting. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows, and Mac.
4. Machine Learning (basic to advanced) -is an add-on to the Data Scientist skill set. ML is a subset of AI that contributes to the modeling of data. It uses algorithms like K-nearest neighbors, Random Forests, Naïve Bayes, and Regression Models.
5. Machine Learning with Python - Machine learning is a growing technology that enables computers to learn automatically from past data. Machine learning uses various algorithms for building mathematical models and making predictions using historical data or information. Machine Learning is a subset of AI that is mainly concerned with the development of algorithms that allow a computer to learn from the data and past experiences on their own.
6. Deep Learning Foundation - Deep learning is also known as deep structured learning, is a subset of machine learning and refers to neural networks that have the ability to learn the input data increasingly abstract representations. Artificial Intelligence and Deep Learning are revolutionizing technology, business, services, and industry in a manner not seen before. This has been possible due to rapid progress and strides made in the computing and graphics processor technologies and the widespread use of the internet and mobile devices.
7. Deep Learning with Keras essentially means training an Artificial Neural Network (ANN) with a huge amount of data. In deep learning, the network learns by itself and thus requires humongous data for learning.
8. Keras, it is high-level neural networks API that runs on top of TensorFlow an end to end open source machine learning platform. Using Keras, easily define complex ANN architectures to experiment on your big data.This course, Deep Learning with Keras will get up to speed with both the theory and practice of using keras to implement deep neural networks.

Software engineers who are curious about data science and about the Deep Learning Buzz and data scientists who are familiar with Machine learning and want to develop a strong foundational knowledge of deep learning.

Everyone

Passion and Determination to achieve your goals!!!

• Data Scientist
• Senior Data Scientist
• Senior Data Science Engineer
• Machine Learning Engineer
• Data Analyst
• Python with Data Science - Trainer
• Lead Data Scientist
• Software Engineer (Data Scientist)
• Data Scientist - Machine Learning
• Principal Data Scientist
• Associate Data Scientist
• People Data Scientist
• Business Analysts - Data Scientist
• Deep Learning Engineer
• Data Consultant
• Data Science Developer

Uplatz Certificate of Completion

Digital certificate - Included