Sign up now for our January 2025 Data Analytics training cohort!
The Advanced Data Analytics course is designed for individuals who already possess a basic understanding of data analytics and wish to deepen their expertise in the field. Over 6 months, you will delve into more advanced topics and gain proficiency in cutting-edge data analytics tools and techniques.
Course fee
₦ 600,000 ₦ 450,000
Start a career in data analytics as you enroll in this advanced-level course
Unlock the power of advanced data analytics with our flexible online training program. Dive into engaging pre-recorded videos at your own pace, and join live weekend sessions led by industry experts. Gain practical skills and insights to excel in the world of data analysis.
What You Will Learn;
Advanced Tools and Techniques: Master advanced features of tools such as Google Cloud BigQuery, SQL, Python, Power BI, and Google Sheets to efficiently gather, clean, manipulate, and analyze large, complex datasets.
Develop the ability to analyze and interpret complex data sets to extract meaningful insights and trends, enabling informed and data-driven business decisions.
Enhance your problem-solving and critical thinking skills through hands-on analysis of real-world data sets. Practice identifying key insights, drawing conclusions, and recommending actionable strategies based on data analysis.
Apply your skills and knowledge to real-world data analytics projects. Work on hands-on projects that simulate industry scenarios, allowing you to gain practical experience and build a portfolio of work-ready projects.
Course Summary
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COURSE LEVEL
Data Analytics - Advanced
COURSE DURATION
6 Months + 2 Weeks Guided Project
MODE OF TRAINING
Online & Physical Classes
TRAINING TIME
Weekdays
Morning 10am - 12pm
Evening 3pm - 5pm
Weekend Classes
Evening 4pm - 6pm
TRAINING FEE
Online: ₦ 500,000 ₦ 350,000
Physical: ₦ 600,000 ₦ 450,000
Course outline for our Data Analytics course - advanced level
Our Advanced Data Analytics course curriculum is designed to elevate your skills and proficiency in the field of data analysis. From mastering advanced Spreadsheet techniques to harnessing the power of Python programming for data manipulation, visualization, and analysis, this comprehensive program covers a wide range of topics essential for advanced data analytics professionals.
Advanced Data Manipulation Techniques:
Unlock the full potential of Excel with advanced data manipulation techniques. Learn how to efficiently clean, transform, and structure your data for analysis using powerful tools and methodologies.
Advanced Functions and Formulas:
Dive deeper into Excel's extensive library of functions and formulas. Discover advanced techniques for data analysis, including array formulas, advanced lookup functions, and statistical functions, to tackle complex analytical challenges with ease.
Data Analysis Tools and Features in Excel:
Explore Excel's built-in data analysis tools and features to uncover insights from your data. From pivot tables and conditional formatting to data validation and what-if analysis, master the tools that will enhance your data analysis capabilities and streamline your workflow.
Advance Data Visualization Techniques:
Elevate your data visualization skills with advanced techniques in Power BI. Learn how to create interactive and engaging visualizations, including custom visuals, hierarchies, and slicers, to effectively communicate insights from your data.
Advance Data Modeling and Transformation:
Master advanced data modeling and transformation techniques in Power BI. Explore techniques for building complex data models, including relationships, calculated columns, and measures, and learn how to optimize your data for analysis and visualization.
Customization and Optimization of Power BI Dashboards:
Customize and optimize your Power BI dashboards for maximum impact. Discover advanced dashboard design principles and best practices, including layout design, interactivity, and performance optimization, to create compelling and insightful dashboards that drive actionable insights.
Complex SQL Queries and Subqueries:
Master complex SQL querying techniques to extract valuable insights from your database. Learn how to write advanced SQL queries and subqueries to filter, join, and manipulate data from multiple tables, enabling you to solve complex analytical challenges efficiently.
Data Aggregation and Grouping:
Explore advanced data aggregation and grouping techniques in SQL. Dive deep into aggregate functions, such as SUM, AVG, and COUNT, and learn how to group data effectively to perform insightful analysis and generate meaningful summaries of your data.
Advanced Database Management Techniques:
Enhance your database management skills with advanced SQL techniques. Discover how to optimize database performance, manage indexes and constraints, and implement advanced database administration tasks to ensure the integrity, security, and efficiency of your database system.
Introduction to Python for Data Analysis:
Kickstart your journey into Python for data analysis. Explore the fundamentals of Python programming language, its syntax, and basic data structures, and understand how Python is used in the context of data analytics.
Data Handling and Manipulation with Pandas:
Dive into data manipulation and analysis with Pandas, the powerful Python library for data manipulation and analysis. Learn how to load, clean, filter, and transform data using Pandas data structures and functions, and master advanced techniques for handling complex datasets.
Data Visualization with Matplotlib and Seaborn:
Unlock the power of data visualization in Python with Matplotlib and Seaborn. Discover how to create a wide range of static and interactive visualizations, including line plots, scatter plots, bar charts, and heatmaps, to effectively communicate insights from your data.
Advanced Probability Theory:
Delve into advanced probability theory concepts essential for data analytics. Explore topics such as conditional probability, Bayes' theorem, and probability distributions, and learn how to apply probabilistic principles to analyze uncertain outcomes and make informed decisions.
Statistical Inference and Hypothesis Testing:
Master the art of statistical inference and hypothesis testing to draw meaningful conclusions from data. Learn how to formulate and test hypotheses, conduct significance tests, and interpret results to make informed decisions based on statistical evidence.
Advanced Regression Analysis and Modeling:
Deepen your understanding of regression analysis and modeling techniques for predictive analytics. Explore advanced regression models, including multiple regression, logistic regression, and time series analysis, and learn how to build and evaluate models to uncover relationships and patterns in your data.
To enroll in our advanced data analytics training, we require individuals to have intermediate knowledge and experience in the field. This ensures that participants are adequately prepared to tackle the advanced concepts and topics covered in the course. Here are the prerequisites for enrolling in our advanced training:
Intermediate Knowledge in Data Analytics.
Completion of Beginners Level Training (or Equivalent).
Practical Experience in Data Analytics
Proficiency in Relevant Tools and Technologies
Commitment to Continuous Learning
Possess a reliable and functional laptop, meeting minimum system requirements.
Maintain consistent internet access.
Commit to attending classes every weekend, from 4:00 pm to 6:00 pm, throughout the training period.
Minimum System Configuration for Data Analysis:
Operating System: Windows 10 or macOS Catalina (or later)
Processor: Intel Core i5 or equivalent
RAM: 8 GB
Storage: 256 GB SSD
Internet Connection: Broadband or High-speed connection recommended for online classes and data access.
Software: Microsoft Excel, Google Sheets, or any preferred spreadsheet software. Optionally, Power BI, Tableau, Anaconda, or SQL tools may be utilized based on course requirements.
Advanced skills in data analytics open up diverse career opportunities across various industries. In addition to the skills highlighted under the "beginners" level, some other common career paths for individuals with advanced skills in data analytics include:
Data Scientist: Data scientists utilize advanced analytical techniques, machine learning algorithms, and statistical models to extract insights from data and drive business decisions. They are responsible for analyzing complex datasets, developing predictive models, and generating actionable insights to solve business problems.
Business Intelligence Analyst: Business intelligence analysts focus on analyzing data to provide insights that support strategic decision-making and business planning. They design and develop dashboards, reports, and data visualizations to track key performance indicators and monitor business performance.
Data Engineer: Data engineers design, build, and maintain data infrastructure and systems that enable the storage, processing, and analysis of large volumes of data. They work with advanced data management technologies and tools to ensure data quality, reliability, and scalability.
Machine Learning Engineer: Machine learning engineers design and implement machine learning models and algorithms to solve complex problems and automate processes. They work with advanced programming languages, such as Python or R, and machine learning frameworks to develop predictive models and algorithms.
Business Analyst: Business analysts bridge the gap between business objectives and data-driven insights. They analyze business processes, identify opportunities for improvement, and leverage data analytics to recommend strategies for enhancing efficiency, profitability, and performance.
Data Consultant: Data consultants provide strategic advice and consulting services to organizations looking to leverage data analytics to drive business growth and innovation. They offer expertise in data strategy, analytics implementation, and organizational transformation to help clients unlock the value of their data assets.
Payment Plans
At Datafied Academy, we provide a versatile payment option for our data analytics courses. You have the flexibility to either pay the training fee in a single payment or opt for a two-installment plan.
Pay in installments 60%-40%
Before the commencement of the training, you'll be allowed to pay 60% of the training fee, then after 1 month into the training, you pay up the remaining 40%.
Pay in full 100%
If you have the capacity to pay up the entire training fee before the commencement of the training, then this option is for you.
Datafied Academy is a top-tier institution specializing in data analytics training, dedicated to empowering individuals with the necessary skills to succeed in the dynamic field of data analytics.
