Description:

This course provides a comprehensive understanding of data analysis techniques, tools, and methodologies used to derive meaningful insights from large datasets. Students will gain hands-on experience in various data analysis processes, including data cleaning, data visualization, statistical analysis, and predictive modeling. The course also covers advanced topics in data analysis such as machine learning algorithms and data mining techniques.

Course Duration:

• This is a LIVE Online Course.
• Course Duration: 3 Months
• Classes: 3 days in a week of 1.5 hours each

Pre-requisite: 

• No Pre-requisite required. Curiosity to learn. No IT background is required

Who is this course for?

• People looking to advance their career in Data Science and Data Analytics.
• Those who wants to switch their career into IT from Non-IT background.
• Want to make base strong before moving to Machine Learning, Deep Learning, Reinforcement Learning, NLP, and other AI courses.

Key Highlights:

• Master data analysis techniques using popular tools like R and Python
• Learn to clean, transform, and preprocess raw data for analysis
• Gain expertise in visualizing data using charts, graphs, and interactive dashboards
• Apply statistical methods and hypothesis testing to make data-driven decisions
• Develop predictive models using machine learning algorithms
• Explore advanced data analysis concepts like clustering and regression analysis

What you will learn:

• Learning Outcome 1
  Understand the fundamental concepts of data analysis, including data types, variables, and statistical measures.
• Learning Outcome 2
  Learn to clean and preprocess data by handling missing values, outliers, and inconsistencies.
• Learning Outcome 3
  Visualize data using popular libraries such as Matplotlib and ggplot to gain insights and communicate findings effectively.
• Learning Outcome 4
  Apply statistical techniques like hypothesis testing, correlation analysis, and regression to analyze data and draw meaningful conclusions.
• Learning Outcome 5
  Utilize machine learning algorithms, including decision trees, logistic regression, and k-nearest neighbors, for predictive analysis.
• Learning Outcome 6
  Explore advanced data analysis techniques like cluster analysis, principal component analysis, and time series analysis.

ABOUT TRAINER:

Anoop is a dynamic professional with 15+ years of experience in Human Resource Management, Data Analytics and Artificial Intelligence, Strategic Alliances, Business Development and Consulting. He is passionate for data science, machine learning and artificial intelligence and keep a good analytic acumen approach to decision making.

He has done Post Graduation in Business Analytics from Great Lakes and certified in Advanced HR Analytics from Singapore Management University. He also holds a Master's Degree in Human Resources from Bharati Vidhyapeeth, IMED, Pune and Bachelor's degree in Maths from Delhi University. Anoop is Fitness Savvy and enjoy sports.

He has trained more than 1000+ students on Data Science through Online and offline training methodologies and continuing further!