Data Science Course Curriculum

• Modules 5
• Projects 12⁺
• Duration 14 Weeks
• Skill level Advance
• Language English
• Students 171
• Assessments Yes
• Hybrid classes Yes
• Certification Yes

Course Description

Data scientist is one of the best suited professions to thrive 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. And how can you do that? Universities have been slow at creating specialized data science programs. (not to mention that the ones that exist are very expensive and time consuming).
Most online courses focus on a specific topic and it is difficult to understand how the skill they teach fit in the complete picture

Certification

Your certification will be based on your ability to applies mathematical, problem-solving, and coding skills to manage big data, extracting valuable insights. The certificate will portraite you as a professional Data Scientist.

Learning Outcomes

• The course provides the entire toolbox you need to become a data scientist
• Understand the mathematics behind Machine Learning
• Perform linear and logistic regressions in Python
• Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
• Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
• Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
• Unfold the power of deep neural networks
• Apply your skills to real-life business cases
• Carry out cluster and factor analysi
• Start coding in Python and learn how to use it for statistical analysis
• Learn how to pre-process data

Job Oppurtunities

• Data Analyst
• Data Engineers
• Database Administrator
• Data Engineer
• Machine Learning Engineer
• Data Scientist
• Data Architect
• Statistician
• Business Analyst
• Data and Analytics Manager