Data Analyst

250 Hours / 6-9 Months, Evening course

This part-time Data Analyst (BI Analyst) program features expert instruction, hands-on projects, AI-driven analytical methodologies, and a real connection to the industry to get graduates hired.

In today’s digital ecosystem, where web and mobile applications orchestrate most aspects of our lives, data reigns supreme. Each digital interaction leaves a trace, allowing corporations to accumulate and analyze massive amounts of both personal and business data. This ‘Big Data’ usage is driving transformative changes across all sectors, from navigation systems to healthcare and cybersecurity.

Over the past few years, new roles like Data Analysts and Data Scientists have emerged. Data Analysts, also known as Business Intelligence (BI) Analysts, scrutinize large datasets to discern patterns. These patterns subsequently guide strategic business decisions. Crucially, our program integrates the use of advanced Artificial Intelligence tools in the training process, enabling learners to understand and apply AI-driven analytical methodologies to harness the power of data effectively.

Teach Students to Solve The World’s Most Interesting Problems

Graduates will become indispensable to employers with data analysis fluency. Graduates will harness the predictive power of data to work at the forefront of diverse industries like public policy, robotics, and FinTech. They will learn to use the latest AI tools to get data analysis better and faster.

Open Doors With Industry Connections

Equip students to succeed in a rapidly expanding field with help from our network of data experts, instructors, hiring partners, and alumni. The Data Analyst curriculum was created in collaboration with the industry’s leading companies to make our programs as relevant as possible to the local industry’s needs, assuring graduates will be job-ready as soon as the program ends.

Guide Students to Deliver a Professional Project

Throughout the program, practical skills are acquired through the completion of projects that tackle real-world data problems from end to end. Students will gain hands-on experience with market-leading technologies, processing information, data analysis capabilities, business intelligence, and more, compiling a portfolio of projects designed to reinforce what students have learned in each unit.

Who Is the Program For?

Driven and motivated individuals, with or without tech background, who wish to launch a highly sought-after career as a Data or BI Analyst.

Candidates for the program are required to have basic Microsoft Excel skills.

Top Notch Professionals

This unique program was built by a professional team made up of the leading experts in Data Science and Analytics, with vast knowledge and experience in training too.

Eran Lasser

CEO of Wawiwa

Eran is a tech education entrepreneur with over 20 years of experience. Eran founded and managed four IT training companies: John Bryce Training (Israel), TRIG (China), JB-IQsoft (Hungary), KocBryce (Turkey). Eran also partnered to establish DAN.IT Education (Ukraine), Techub (Georgia), and more. In addition, Eran managed Mentergy, which provides e-learning and distance learning solutions. Over the years, he was responsible for the reskilling of more than 50,000 individuals now working as tech professionals.

Daniel Anderson

Chief Training Officer

Daniel is responsible for updating state-of-the-art topics in the company’s tech training programs, and for maintaining its training methodologies. Daniel was the Chief Trainer at the Israel Defense Force’s Tech Training Center and is a graduate of the IDF training process. He develops and delivers a wide range of programming courses, and is a Full-Stack Developer and Data Scientist.

Talia Morchi

Head of Data Analyst Program

Talia has over 10 years of experience in the IT industry, having held the roles of Product Manager, Project Manager, and Data Solutions Manager, where she specialized in data analysis in addition to her other responsibilities. She is a lecturer at Bar Ilan University, serving as the director of the BI Developer course and also teaching in the Data Science course. In addition, she is an undergraduate lecturer at Ono and the academic director and leading lecturer of the data analyst track at the G-Academy. Talia is an expert in various development tools, including SQL, Python, Excel, and uniPaaS.

What Do Graduates Have to Say?

Program Curriculum

  • General introduction
  • Relational database
  • KPI
  • Analyst work circle
  • Introduction to relational database 
  • Insights that can be derived from the data
  • Introduction to SQL
  • Introduction to work environment 
  • Basic SQL query 
  • Calculated columns
  • Data normalization​
  • Basic and most common built-in functions
  • Sorting the results 
  • Grouping and aggregate  
  • Advance filtering 
  • Working with NULL values 
  • Diagram 
  • Join tables
  • Conditional statement 
  • Correlated and non-correlated subqueries 
  • Documentation​​
  • Window functions 
  • CTE (Common Table Expression) 
  • DML (Data Manipulation Language) 
  • DDL (Data Definition Language) 
  • Data analysis using analyst work circle 
  • Writing user scalar functions 
  • Temporary tables and stored procedures
  • Introduction to Large Language Models (LLMs)
  • Practical Demonstration for SQL
  • Impact of AI and LLMs on Data Learning & Control
  • Will human Data Analysts be replaced by AI?
  • Formulas 
  • Basic and advanced filtering data 
  • Sorting data 
  • Commonly used built-in functions
  • Connectivity to outer data source 
  • IF functions
  • VLOOKUP
  • Error handling 
  • MSSQL​
  • What-IF analysis and conditional formatting   
  • Pivot charts and tables ​​
  • Slicers 
  • Dashboarding
  • Introduction to Power BI
  • Introduction to Power Query
  • Preliminary data handling
  • Modeling and DAX (Data Analysis Expressions)
  • Data visualization
  • Basic and advanced chart types​
  • Combo chart 
  • Dual axis
  • Filtering 
  • Sorting 
  • Hierarchy 
  • Total and subtotals 
  • Calculated fields 
  • Custom aggregations 
  • Logic statements 
  • Dashboards 
  • Exporting a dashboard
  • Python fundamentals 
  • Basic operations and use of operators 
  • Variables and basic data types 
  • Python basic build in functions 
  • String slicing 
  • Conditions 
  • Introduction to Pandas package 
  • Import data from CSV  
  • Pandas data structures: DataFrame, Series 
  • Pandas descriptive methods (head (), tail (), info (), describe () etc.)
  • Filter records by conditions  
  • Complex conditions
  • Sorting data
  • Retrieving data 
  • Handling NULL values 
  • Update data 
  • Grouping and aggregation
  • Pivot table
  • Merging DataFrame methods 
  • Loops: For, While, Loop flow control 
  • Local and global variable 
  • Lambda function 
  • Apply method 
  • Connect to MSSQL 
  • Visualization with Matplotlib 
  • Visualization with Seaborn  
  • Adjusting the graph display 
  • Save data and pictures into Excel file

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