Data Scientist
Award Winning | LABS | 24/7 Access | 100% Pass Rate | 12 Months Subscription | Table/Mobile Compatible.
IT Academy
Summary
- Exam(s) / assessment(s) not included in price, and must be purchased separately
- Tutor is available to students
Overview
Stay ahead of the competition. Register for the Data Analyst to Data Scientist course through IT Academy.
There are 4 Tracks for the Data Analyst to Data Science course (Data Analyst, Data Wrangler, Data Ops and Data Science). Each stage of the journey delivers 40-50 hours of courses + multimodal content and an additional 10-12 Practice Labs, Certification Pre/Assessments.
Career Ready Education. Register today for our award winning Cloud based training courses led by Certified Professionals. 24/7 Access, Mobile Compatible, Student Support - 99% success rate!
Expertise Level: Beginners
Study Time: 12 Months to complete 200 hours eg study 1 hour per day to complete your course in 7 months | Study Full Time or Part Time.
Student support: One-on-One Mentoring
Access your Cloud-Based Learning on a Computer, Laptop, Tablet or Smartphone. Courses are designed in video with audio, printable, includes One-on-One Mentoring for Certification exams.
Courses include:
- 24/7 Access
- Tablet/Smartphone Compatible
- 100% Pass Rate
- Course Mastery Certificate
- 12 Months Subscription
- Student Support
- Printable
Certifications
Microsoft Technology Associate (MTA) Database
Microsoft Certified Azure Fundamentals
Course media
Description
Data Analyst to Data Scientist Course includes:
- MTA FUNDAMENTALS
98-364: MTA Database Fundamentals
- DP-900: Azure Data Fundamentals
DP-900 Azure Data Fundamentals: Data Workloads
DP-900 Azure Data Fundamentals: Data Analytics
DP-900 Azure Data Fundamentals: Relational Data Workloads
DP-900 Azure Data Fundamentals: Relational Data Management
DP-900 Azure Data Fundamentals: Provisioning & Configuring Relational Data Services
DP-900 Azure Data Fundamentals: Azure SQL Querying Techniques
DP-900 Azure Data Fundamentals: Non-relational Data Workloads
DP-900 Azure Data Fundamentals: Non-relational Data Services
DP-900 Azure Data Fundamentals: Azure Cosmos
DP-900 Azure Data Fundamentals: Non-relational Data Management
DP-900 Azure Data Fundamentals: Azure Analytics Workloads
DP-900 Azure Data Fundamentals: Modern Data Warehousing
DP-900 Azure Data Fundamentals: Azure Data Ingestion & Processing
DP-900 Azure Data Fundamentals: Azure Data Visualization
- Data Science: Track 1: Data Analyst
Data Science: Data Architecture Primer
Data Science: Data Engineering Fundamentals
Data Science: Python for Data Science
Data Science: R for Data Science
Data Science: Statistics
Data Science: Spark
Data Science: Hadoop
Data Science: Data Silos, Lakes, & Streams
Data Science: Data Analysis Application
- Data Science: Track 2: Data Wrangler
Data Science: Data Wrangling with Pandas
Data Science: Cleaning Data in R
Data Science: Data Tools
Data Science: Trifacta for Data Wrangling Data
Data Science: MongoDB for Data Wrangling
Data Science: Hive
Data Science: Hadoop
Data Science: Spark
Data Science: Data Lake
Data Science: Building Data Pipelines
Data Science: Data Architecture
- Data Science: Track 3: Data Ops
Data Science: Deploying Data Tools
Data Science: Delivering Dashboards
Data Science: Cloud Data Architecture
Data Science: DevOps & Containerization
Data Science: Compliance Issues and Strategies
Data Science: Implementing Governance Strategies
Data Science: Data Access & Governance Policies
Data Science: Streaming Data Architectures
Data Science: Scalable Data Architectures
Data Science: Data Sources
Data Science: Data Ops 16: Securing Big Data Streams
Data Science: Harnessing Data Volume & Velocity
Data Science: Data Rollbacks
- Data Science: Track 4: Data Science
Data Science: Balancing the Four Vs of Data
Data Science: Data Driven Organizations
Data Science: Raw Data to Insights
Data Science: Tableau Desktop: Real Time Dashboards
Data Science: Python for Data Science
Data Science: Data Science Statistics
Data Science: Using Python to Compute & Visualize Statistics
Data Science: R for Data Science – Data Visualization
Data Science: Powering Recommendation Engines
Data Science: Data Insights, Anomalies, & Verification
Data Science: Data Science
Data Science: Machine & Deep Learning Algorithms
Data Science: Creating Data APIs Using Node.js
Requirements
There are no pre-requisites for the Data Analyst to Data Scientist course.
Learners need a computer, laptop or tablet and internet connection, courses are designed in video with audio and coupled with unlimited support.
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This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.
