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Data Analytics

Tools to Master: Excel, Python, SQL, NoSQL, Power BI, Presto, Knime Skills to Master: SQL, Data Wrangling, Prediction Algorithms, Data Visualization Using Power BI, Time Series, Machine Learning, Power BI, Advanced Statistics, Data Minin

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Data Analytics Course Overview
  • Step into the world of Data Analytics with the all-inclusive course offered by Aptech Computer Training, available at our Dubai & Sharjah branches. This comprehensive program is designed to equip learners with essential skills in Data Analysis, Data Wrangling, Data Visualization, Machine Learning, SQL, Python, and Power BI. Gain expertise in building predictive models, performing statistical analysis, and visualizing data insights using the most powerful tools and techniques in the industry.
  • This course offers hands-on training with real-world projects to provide participants with practical knowledge of Data Mining, Predictive Modeling, Data Visualization, SQL/NoSQL Databases, and Machine Learning. With a structured approach to mastering Data Analytics, learners will be able to transform raw data into meaningful insights and drive informed decision-making.
  • At the end of this course, participants will be awarded a KHDA-certified certificate, enhancing their credentials and boosting their career prospects.

Lesson 1: Data Analysis Fundamentals

  • Introduction to Data Science
  • Create and Modify Tables
  • Sort and Filter Data

Lesson 2: Visualizing Data With Excel

  • Visualize Data with Charts
  • Modify and Format Charts
  • Apply Best Practices in Chart Design

Lesson 3: Analyzing Data With Formulas And Functions

  • Analyze Data with Formulas and Named Ranges
  • Analyze Data with Functions
  • Implement Data Validation, Forms, and Controls
  • Create Conditional Visualizations with Lookup Functions

Lesson 4: Analyzing Data With Pivottables

  • Create a PivotTable
  • Analyze PivotTable Data

Lesson 5: Presenting Visual Insights With Dashboards In Excel

  • Visualize Data with PivotCharts
  • Filter Data Using Slicers and Timelines
  • Create a Dashboard in Excel

Lesson 6: Creating Geospatial Visualizations With Excel

  • Create Map Charts in Excel
  • Customize Map Charts in Excel

Lesson 7: Getting And Transforming Data

  • Anaconda Jupyter Environment Setup.
  • Python language Overview.
  • Data types of Python, numbers, string.
  • If, el-if, Loops in python.
  • Functions and modules in python
  • Lambda function.
  • Strings methods.
  • List and its methods.
  • Tuple, set, dictionary and their methods

Lesson 9: Analysis Using Python

  • Understanding the uses of various open source libraries.
  • Importing various modules with different methods.
  • Working with Numpy.
  • Numerical operations on Numpy array.
  • Exploring various use cases of Numpy.
  • Financial Analysis using scikit-learn, QuantLib, SciPy

Lesson 10: Data Visualization Using Python

  • Matplotlib, Seaborne, Plotly and Cufflinks.
  • Draw different types of graphs using above modules.
  • Pie chart, histogram, bar chart, boxplot, count plot etc.

Lesson 11: Data Analytics Using Power Bi

  • Dash Board Preparation with BI.
  • Connect to Kaggle Datasets.
  • Explore Pandas Data Frame.
  • Analyze and manipulate Pandas Data Frame.
  • Data cleaning with Python & Export to BI.
  • Data Visualization with Python.
  • Connect to web data with Power BI.
  • Clean and transform web data with Power BI.
  • Create data visualization with Power BI.
  • Publish reports to Power BI Service.
  • Transform less structured data with Power BI.
  • Connect to data source with excel.
  • Prep query with excel Power query.
  • Data cleaning with excel.
  • Create data model and build relationships.
  • Analyze data with Pivot Tables
  • Analyze data with Pivot Charts
  • Connect to data sources with Power BI
  • Join related data and create relationships with PowerBI

Lesson 12: Presto

  • Introduction to Presto
  • Writing Queries in Presto on large data sets.
  • Data Transformation using Presto

Lesson 13: Data Wrangling With Sql/No Sql

  • Introduction to SQL
  • SQL operators
  • Join, tables, and variables
  • SQL functions
  • Subqueries
  • SQL functions, views, and stored procedures
  • User-defined functions
  • SQL performance and optimization
  • Advanced concepts
  • Cloud Operation Using Fire Base
  • No SQL Schema Using Fire Base
  • Fire Base Migration With Python

Lesson 14: Knime

  • Introduction to KNIME
  • Working with data in KNIME
  • Loops in KNiME
  • Webscraping in KNIME
  • Hyperparameter optimization in KNIME
  • Hyperparameter optimization for Machine Learning Models using loops in KNIME
  • Feature Selection in KNIME

Lesson 15: Predictive Modeling

  • Multiple linear regression
  • Logistic regression
  • Linear discriminant analysis

Lesson 16: Time-Series Forecasting

  • Introduction to time-series
  • Correlation
  • Forecasting
  • Autoregressive models

Lesson 17: Statistics & Machine Learning Using Python

  • Programming with Python
  • Advance Statistics
  • ANOVA
  • Regression analysis
  • Data Mining
  • Supervised and unsupervised learning
  • Clustering
  • Decision trees
  • Neural networks

Who Can Enroll?

  • Aspiring Data Analysts.
  • Business Professionals.
  • Data Enthusiasts.
  • Anyone looking to pursue a career in Data Analytics.

Course Outcomes:

  • Proficiency in data analysis using Excel, Python, and Power BI.
  • Capability to build predictive models and visualize data insights.
  • Expertise in SQL/NoSQL databases for managing data.
  • Skills in Machine Learning for advanced analytics.
  • Hands-on experience with real-world datasets.

Career Opportunities:

  • Data Analyst
  • Business Intelligence Analyst
  • Data Scientist
  • Data Engineer
  • Machine Learning Specialist

Why Choose Us?

  • Expert Instructors: Learn from professionals with practical knowledge in data analysis.
  • Hands-On Training: Practical projects to reinforce your skills.
  • KHDA-Certified Certificate: A valuable credential to enhance your career opportunities.
  • Comprehensive Curriculum: Covering all essential tools and techniques for data analysis.
  • Flexible Learning Options: Available both online and offline.

Eligibility / Requirements:

  • Basic understanding of programming.
  • Familiarity with Excel and Python is helpful but not mandatory.

Notes:

* Course topics and duration may be modified by the instructor based upon the knowledge and skill level of the course participants.

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