Data Sciences Specialization Course

Data Science and Artificial intelligence have transformed the world completely. Organizations around the world are leveraging artificial intelligence to avoid repetitive tasks and improve customer experience. Robots are taking on the world by storm and are continuously building intelligence comparable to human brains. Artificial Intelligence and Machine Learning are the highest-paying jobs in the world. As per a recent estimate, more than 90% of the companies will use artificial intelligence in one way or the other to build or enhance their products and services. These companies are looking for people who are skilled in data science and AI. Unfortunately, the industry is facing an acute shortage of highly skilled people to fill the void.

OMNI ACADEMY Data Sciences Specialization course is designed with meticulous care to provide the learners with a straightforward course path of natural progression in which new topics and concepts are gradually introduced to them and in which they are exposed to interconnected Data Science facets such as Python, Machine Learning techniques, Deep learning and neural networks, Exploratory Data Analysis, Data Visualization, Artificial Intelligence, etc.

Students will get hands-on training in Predictive Analytics, Python, Data Visualization, Data Analytics. Gain in-demand data analytics skills for business success with this Data Science programme.

Data Sciences Summary

Defining Data Science and What Data Scientists Do

In this course, you will go over the course syllabus to learn what will be taught in this course. Also, you will hear from data science professionals to learn what data science is, what data scientists do, and what tools and algorithms data scientists use on a daily basis. Finally, you will be required to complete a reading assignment to learn why data science is considered the sexiest job in the 21st century.

Data Science in Business

In this module, you will learn about what companies need to do in order to start with data science. You will also learn about some of the qualities that differentiate data scientists from other professionals. In addition, you will learn about analytics and what important role data scientists play in this process, and about story-telling and the importance of an effective final deliverable. Finally, you will be required to apply what you learned about data science by answering open-ended questions.

Big Data | Data Sciences Course Overview

Module-01 Machine Learning Data Analysis with Python

Basic Concepts, History and Evolution of Machine Learning for Big Data as a business application domain. Use cases in different business industries for both small and big data. A review of Machine Learning techniques and algorithms and their interpretation from a business perspective. Theoretical and Practical Exposure of Cluster Analysis and Support Vector Machines.

KEY Learning

Python Data Analysis with NumPy and Pandas
Python Data Visualization – Matplotlib and Pandas
Math of Machine Learning – Probability, Regression, Vectors, Matrices, Baysian, K Nearest
Machine Learning with Python – Supervised vs Unsupervised Learning and Train / Test
Data Mining, Big Data with Machine Leaning – Apache Spark
Neural Networks and Deep Learning.
Machine Learning Project – Develop Product Recommender System in Python

Module-02 Understanding Data Science & Data Mining

In this module, you will learn about data science and what skills are required for anyone interested in pursuing a career in this field and as he gives advice to those who are looking to start a career in data science. Finally, you will be required to complete reading assignments to learn about the process of mining a given dataset and about regression analysis.

Data Science Course Key Learning

Introduction and Decision Trees, Typical Data Science Tasks, Data Science Applications/Examples
Prediction techniques Continues: Holdout Method, ROC Curve Interpretation, Artificial Neural Network
Regression and Ensemble Methods: Linear Regression Analysis, Ensemble Methods (Bagging and Boosting), K-Nearest Neighbors Method
Clustering: K-Means Clustering, Hierarchal Clustering, Fuzzy C-Means
Text Analysis: Part of Speech tagging, Bags of Words Creation, Part of Speech and Stop Word Filters, Stemming Text, Term Frequency Count
Market Basket Analysis of Consumer: Association Rule Mining, Apriori Method, Frequent Item sets

Data Sciences Course Audience

This course is primarily for individuals who are passionate about the field of data science and who are aspiring to become data scientists.

Data Science Course Benefits

Individuals who earn this certification were able to describe the Data Science and What Data Scientists Do, how data sciences helping modern business to perform better, understanding data and patterns.

Course Prerequisite

Basic level understanding with any financial data analysis, database or programming language understanding.

Data Sciences Job Roles

The Data Analyst (The data analyst is the Sherlock Holmes of the data science team)
The Data Architect
The Data Engineer
The Statistician
The Database Administrator
The Business Analyst
Data and Analytics Manager

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